Scheme and Syllabi for Eighth Semester CSE
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8/13/2019 Scheme and Syllabi for Eighth Semester CSE
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SCHEME AND SYLLABI FOR
EIGHTH SEMESTER
OF
BACHELOR OF
TECHNOLOGY IN
COMPUTER SCIENCE AND
ENGINEERING
FROM 2009 ADMISSION ONWARDS
CALICUT UNIVERSITY (P.O), THENHIPALAM
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Semese! /III Hours / Week Marks
Code SubjectL T D/P
Inte-rnal
Semes
ter-
end
Semester-
end
duration-hours
Credits
CS!" 0!# Com2uter 7rchitecture andParallel Processin$
( # &! '! & *
CS!" 0!% Data minin$ and Warehousin$ % # &! '! & &
CS!" 0!& Electi.e I4 & # &! '! & (
CS!" 0!( Electi.e 4 & # &! '! & (
C&09 0*(P) Pro.ect ## '
C&09 0-(P) &eminar & %
C&09 0'(P) /i%a /oce &
To$% )2 1 )1 2,
To$% M$!-s
Code E%e&ie I
CS!" L!# Inormation Securit)
CS!" L!% Com2utational Intelli$ence
CS!" L!& 8ueuin$ Theor)
CS!" L!( 5bject 5riented Modelin$ and Desi$n
CS!" L!* Mana$ement Inormation S)stems
E%e&ies #o! 0'
$nd ,'
semese!CS!" L!+ 7rtiicial eural et3orks
CS!" L!' Distributed S)stems
CS!" L!0 9u66) Lo$ic and 722lications
CS!" L!" S2eech and Lan$ua$e Processin$
CS!" L#! 7d.anced To2ics in 52eratin$ S)stems
CS!" L## 7d.anced Database Desi$n
CS!" L#% Di$ital Ima$e Processin$
CS!" L#& 4LSI Desi$n
CS!" L#( Inormation Theor) and Codin$
CS!" L#* MultimediaCS!" L#+ Web Pro$rammin$
CS!" L#' 1ra2h Theor) and Combinatorics
CS!" L#0 Machine Learnin$
CS!" L#" Sot Com2utin$
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CS!" L%! Inormation :etrie.al
CS!" L%# Di$ital Desi$n ;sin$ 4HDL
CS!" L%% Com2utational 1eometr)
CS!" L%& Simulation and Modelin$ "G%ob$% E%e&ie ) #!om CSE(
CS!" L%( Com2uter ,ased umerical Methods "G%ob$% E%e&ie 2 #!om CSE(
CS!" L%* Pattern :eco$nition "G%ob$% E%e&ie + #!om CSE(
G%ob$% E%e&ies #!om o'e! de3$!mens
EE!" L%& Process Control and InstrumentationEE!" L%* :obotics < 7utomation
ME!" L%( Marketin$ Mana$ement
7!" L%( Project Mana$ement
EC!" L%* ,iomedical Instrumentation
IC!" L%& ,io-Inormatics
PE!" L%& Total 8ualit) Mana$ement
CE!" L%( :emote Sensin$ and 1IS
CE!" L%* 9inite Element Methods
,T!" L%( ,io-ethics and Intellectual Pro2ert) :i$hts
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CS!" 0!# = Com2uter 7rchitecture and Parallel Processin$
Objectives
To teach ideas on parallel computing based computer architectures with a quantitative
approach.
To impart concepts in new design paradigms to achieve parallelism memory hierarchy
design and inter&connection networks.
Mod4%e I "). 'o4!s(9undamentals - task o a com2uter desi$ner - trends in technolo$) usa$e and cost - 2erormancemeasurement - Buantitati.e 2rinci2les o com2uter desi$n - instruction set architectures - classiication -addressin$ and o2erations - encodin$ an instruction set - role o com2ilers - case stud) - the DLNarchitecture - 2i2elinin$ - 2i2eline or DLN - 2i2eline ha6ards - data and control ha6ards - im2lementation
diiculties - 2i2elinin$ 3ith multic)cle o2erationsE
Mod4%e II ")* 'o4!s(Instruction le.el 2arallelism - conce2ts and challen$es - d)namic schedulin$ -d)namic hard3are 2rediction -multi2le issue o instructions - com2iler and hard3are su22ort or ILP - .ector 2rocessin$ - .ector
architecture A .ector len$th and stride - com2iler .ectori6ation - enhancin$ .ector 2erormance
Mod4%e III ")0 'o4!s(Memor) hierarch) desi$n - reducin$ cache misses and miss 2enalt) reducin$ hit time - main memor) -.irtual memor) and its 2rotection - case stud) - 2rotection in the Intel Pentium - crosscuttin$ issues - I/5s)stems - 2erormance measures - reliabilit) and a.ailabilit) - desi$nin$ an I/5 s)stem - case stud) -2erormance o ;ni@ ile s)stemE
Mod4%e I/ ")0 'o4!s(Interconnection net3orks - sim2le net3orks - connectin$ more than t3o com2uters - 2ractical issues -multi2rocessors - introduction A a22lication domains - centralised-shared memor) and distributed-sharedmemor) architectures - s)nchronisation - models o memor) consistenc)
Te$&'in8 s&'eme C!edis5*( hours lecture and # hour tutorial 2er 3eek
Text Books#E Hennes) ELE < Pattersen DE7E $omputer Architecture, A Iuantitative approach Harcourt
7sia Pte LtdE >Mor$an Gauman?E
Re#e!en&e Boo-s
#E CE Pattersen DE7E < Hennes) ELE $omputer Drganisation and 5esign, The
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE#!I - :e$ularit) in the class
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least oneBuestion rom each module and not more than t3o Buestionsrom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not more
than t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" 0!%= Data Minin$ and Warehousin$
Objectives
To give only a broad yet in&depth overview of the field of data mining and warehousing a multi&
disciplinary field of study.
Mod4%e I ")0 'o4!s(Introduction= 3hat is Data Minin$/ 3hich data/ 3hat kinds o 2atterns can be mined-Data Warehouse and5L7P technolo$) or Data Minin$/Data Warehouse 7rchitecture
Data 2re2rocessin$= data cleanin$/ data inte$ration and transormation/ data reduction/ discreti6ation andconce2t - hierarch) $eneration
Mod4%e II ")0 'o4!s(Data Minin$ Primiti.es/ Lan$ua$es and S)stem 7rchitectures - Conce2t Descri2tions= Characteristic and
Discriminant rulesData 1enerali6ation - Minin$ 7ssociation :ules in Lar$e Databases - Transactional databases
Mod4%e III ")0 'o4!s(Conce2t Descri2tions= Characteristic and Discriminant rules/ Data 1enerali6ation/ E@am2le o decisiontables and :ou$h SetsClassiication and 2rediction/ Decision Tree Induction >ID&/ C(*?/ ,a)esian ClassiicationCluster 7nal)sis 7 Cate$ori6ation o major Clusterin$ methodsMod4%e I/ "9 'o4!s(Introduction to Data 3arehousin$= eed or 3arehousin$/ Data 3arehouse 7rchitecture and desi$n/Hard3are and o2erational desi$n/ Tunin$ and testin$
Trends / De.elo2ments and 722lications
Te$&'in8 s&'eme C!edis5&% hours lecture and # hour tutorial 2er 3eek
Text Books# Han and M Gamber/5ata mining, $oncepts and Techniques/ Else.ier Science/ %!!'
Re#e!en&e Boo-s# GPSoman/ Sh)am Di3akar/ and 4 7ja)/"nsight into 5ata Mining, Theory and *ractice/
Prentice Hall o India/ %!!+% S Sumathi/ S Si.anandam/"ntroduction to data mining and its applications%"llustrated
Edn)/ S2rin$er Publishers/ %!!+& PMTan/ Stenbach and 4Gumar/"ntroduction to 5ata Mining/ Pearson Education/ London/
%!!'( GMehmed/5ata Mining, $onceptsModels Methods and Algorithms/ ohn Wile) and Sons/
%!!&* Paulraj Ponniah/5ata Carehousing Fundamentals, A $omprehensive 8uide for "T *rofessional/
Wile) Student Edition/ %!!'+ S 7nahar) and D Murra)/5ata Carehousing in the +eal Corld,A *ractical 8uide for
3uilding 5ecision -upport -ystems/ Pearson Education/ %!!!' MH Dunham/5ata mining, "ntroductory and Advanced Topics/ Pearson Education/ %!!(
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE#!I - :e$ularit) in the class
Noe5 5ne o the assi$nments shall be simulation o continuous s)stems usin$ an) technicalcom2utin$ sot3are
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least oneBuestion rom each module and not more than t3o Buestionsrom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not morethan t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" 0!* >P? = Project
Objectives
This 2roject 3ork is the continuation o the 2roject initiated in se.enth semester The 2erormance o
the students in the 2roject 3ork shall be assessed on a continuous basis b) the 2roject e.aluation committeethrou$h 2ro$ress seminars and demonstrations conducted durin$ the semester Each 2roject $rou2 shouldmaintain a lo$ book o acti.ities o the 2roject It should ha.e entries related to the 3ork done 2roblemsaced solution e.ol.ed etc
There shall be at least an Interim E.aluation and a inal e.aluation o the 2roject in the 0thsemesterEach 2roject $rou2 has to submit an interim re2ort in the 2rescribed ormat or the interim e.aluation
Each 2roject $rou2 should com2lete the 2roject 3ork in the 0thsemester Each student is e@2ected to2re2are a re2ort in the 2rescribed ormat based on the 2roject 3ork Members o the $rou2 3ill 2resent the
rele.ance desi$n im2lementation and results o the 2roject beore the 2roject e.aluation committeecom2risin$ o the $uide and three/our acult) members s2ecialised in com2uter science and en$ineerin$
*! o the marks is to be a3arded b) the $uide and *! b) the e.aluation committee
Te$&'in8 s&'eme C!edis5%& hours 2ractical 2er 3eek
Ine!n$% Conin4o4s Assessmen
(! - Desi$n and de.elo2ment/Simulation and anal)sis&! - Presentation < demonstration o results
%! - :e2ort#! - :e$ularit) in the class
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CS!" 0!+ >P? = Seminar
Objectives
To assess the ability of the student to study and present a seminar on a topic of current relevance in
computer science engineering or allied areas
It enables the students to $ain kno3led$e in an) o the technicall) rele.ant current to2ics and
acBuire the conidence in 2resentin$ the to2ic The student 3ill undertake a detailed stud) on the chosen
to2ic under the su2er.ision o a acult) member b) reerrin$ 2a2ers 2ublished in re2uted journals and
conerences Each student has to submit a seminar re2ort based on these 2a2ersM the re2ort must not be
re2roduction o an) ori$inal 2a2er 7 committee consistin$ o three/our acult) members 3ill e.aluate the
seminar
Te$&'in8 s&'eme C!edis5%& hours 2ractical 2er 3eek
Ine!n$% Conin4o4s Assessmen%! - :ele.ance o the to2ic and literature sur.e)*! - Presentation and discussion%! - :e2ort
#! - :e$ularit) in the class and Partici2ation in the seminar
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CS!" 0!' >P? = 4i.a 4oce
Objectives
To examine the knowledge acquired by the student during the 3.Tech. course through an oral
examination
The students shall 2re2are or the oral e@amination based on the theor) and laborator) subjects
studied in the ,ETechE Course mini 2roject seminar and 2rojectE There is onl) uni.ersit) e@amination or
.i.a-.oceE ;ni.ersit) 3ill a22oint t3o e@ternal e@aminers and an internal e@aminer or .i.a-.oceE These
e@aminers shall be senior acult) members ha.in$ minimum i.e )ears teachin$ e@2erience at en$ineerin$
de$ree le.elE 9or inal .i.a-.oce candidates should 2roduce certiied re2orts o mini 2roject seminar and
2roject >t3o interim re2orts and main re2ort?E I he/she has under$one industrial trainin$/industrial
.isit/educational tour or 2resented a 2a2er in an) conerence the certiied re2ort/technical 2a2er shall also
be brou$ht or the .i.a-.oceE
7llotment o marks or .i.a-.oce shall be as $i.en belo3E
C!edis5&
Assessmen in /i2$92o&e
(! - Subjects&! - Project and Mini Project%! - Seminar#! - Industrial trainin$/industrial .isit/educational tour or Pa2er 2resented at ational-le.el
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE#!I - :e$ularit) in the class
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least oneBuestion rom each module and not more than t3o Buestionsrom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not morethan t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE#!I - :e$ularit) in the class
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least oneBuestion rom each module and not more than t3o Buestions
rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not morethan t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L!&= 8ueuin$ Theor)
Objectives
To teach the fundamental queueing models and the various parameters involved with performance
of the individual disciplines.
Mod4%e I ")1 'o4!s(Descri2tion o the 8ueuein$ 2roblem - Characteristics o 8ueuein$ 2rocesses - otation - Measurin$
S)stemPerormance - Some 1eneral :esults - Sim2le ,ookkee2in$ or 8ueues - Poisson 2rocess and theE@2onential Distribution - Marko.ian 2ro2ert) o the E@2onential Distribution - Stochastic Processes andMarko. Chains - Stead)-state ,irth-Death Processes - Sim2le Marko.ian ,irth-Death 8ueuein$ Models -
Mod4%e II ")* 'o4!s(Stead)-state solution or the M/M/# Model - Methods o Sol.in$ Stead)-state Dierence EBuations -8ueues 3ith 2arallel channels >M/M/c? - 8ueues 3ith Parallel Channels and Truncation >M/M/c/G? -
Erlan$Ks 9ormula >M/M/c/c? - 8ueues 3ith ;nlimited Ser.ice - 8ueues 3ith Im2atience - Transient,eha.iour - ,us)-Period anal)ses or M/M/# and M/M/c - ,ulk in2ut >MR@/M/#? - ,ulk Ser.ice>M/MR/#? - Erlan$Ks Models >M/Ek/# Ek/M/# Ej/Ek/#? - Priorit) 8ueue disci2lines
Mod4%e III ")2 'o4!s(Series 8ueues - 52en ackson et3orks - Closed ackson et3orks - C)clic 8ueues - E@tensions oackson et3orks - on-ackson et3orks - Sin$le-ser.er 8ueues 3ith Poisson In2ut and 1eneral Ser.ice>M/1/#? - Multi ser.er 8ueues 3ith Poisson in2ut and 1eneral Ser.ice - 1eneral In2ut and E@2onential
ser.ice
Mod4%e I/ ")+ 'o4!s(1/Ek/# 1>k?/M/# and 1/PHk/# - 1eneral In2ut 1eneral Ser.ice >1/1/#? - Multichannel 8ueues 3ithPoisson in2ut and Constant Ser.ice >M/D/c? - Semi-Marko. and Marko. :ene3al Processes in 8ueuein$ -5ther 8ueuein$ Disci2lines - Desi$n and Control o 8ueues - Statistical Inerence in 8ueuein$ - ,ounds722ro@imations umerical TechniBues and Simulation - ,ounds and IneBualitites - 722ro@imations -umerical TechniBues - Discrete-E.ent Stochastic Simulation Problems
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# Donald 1ross < Carl M HarrisFundamentals of Iueuing Theory 'rd edition Wile) India
#""'
Re#e!en&e Boo-s# Tri.edi G S*robability and -tatistics with +eliability Iueueing and $omputer -cience
Applications Prentice Hall o India #"0(% 7llen 7 5 Probabilit) -tatistics and Iueueing Theory 7cademic Press #"0#& ,ala$urus3am) E+eliability Engineering Tata Mc1ra3 Hill Publishers e3 Delhi #"0(
( Sanja) G ,oseAn "ntroduction to Iueueing -ystems Gul3er 7cademic Plenum Publishers
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE#!I - :e$ularit) in the class
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least oneBuestion rom each module and not more than t3o Buestionsrom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not morethan t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er one
BuestionE
Maximum Total Marks, 6(
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CS!" L!( = 5bject 5riented Modellin$ and Desi$n
Objectives
To impart ideas on building systems through the ob:ect oriented modelling approach using the
@nified Modelling #anguage.
Mod4%e I ")1 'o4!s(Introduction to ;ML and ;niied Process - ;se case modelin$= 7ctors and ;se cases/ ;se cases2eciication/ 7ctor $enerali6ation/ ;se case $enerali6ation - 5bjects and classes/ :elationshi2s/ Inheritanceand Pol)mor2hism/ Packa$es
Mod4%e II ")1 'o4!s(;se case reali6ation= Interactions/ SeBuence dia$rams/ Communication dia$rams/ Interaction occurrences7cti.it) dia$rams= 7cti.it) semantics/ acti.it) 2artitions/ Sendin$ si$nals and acce2tin$ e.ents/ Interactiono.er.ie3 dia$rams
Mod4%e III ")+ 'o4!s(Desi$n= Desi$n 3orklo3/ 3ell-ormed desi$n classes/ :einin$ anal)sis relationshi2s Interaces andcom2onents - State machine dia$rams/ Com2osite states/ submachine states
Mod4%e I/ ")+ 'o4!s(Im2lementation 3orklo3/ De2lo)ment/ Introduction to 5CL= Wh) 5CL 5CL e@2ression s)nta@/ T)2es o
5CL e@2ressions Introduction to Sot3are 7rchitecture/ 7rchitecture descri2tion lan$ua$e >7DL?
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# im 7rlo3 and Ila eustadt/ @M# 0 and the @nified *rocess, *ractical Db:ect oriented Analysis
and 5esign -econd Edition/ Pearson Education
Re#e!en&e Boo-s# Crai$ Larman/Applying @M# and *atterns 'rd EditionPearson Education% 1rad) ,ooch/ ames:ambau$h/I.ar acobson 7W / The @nified Modeling #anguage @ser
8uide& ,rue$$e/ Db:ect Driented -oftware Engineering using @M# patterns and Hava/ Pearson
Education( ames :ambau$h et al/ Db:ect Driented Modelling and 5esign/ Prentice Hall India
* I.ar acobson/ 1rad) ,ooch/ ames :ambau$h 7W/ The @nified -oftware 5evelopment*rocess
+ DeLillo Db ect Driented 5esi n in $== Thomson Learnin
Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+! - Tests >minimum %?
&! - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etc#! - :e$ularit) in the class
http://www.indiastudychannel.com/resources/37546-CUSAT-B-TECH-Degree-Course-Sem-VI-TOOL.aspx#%23http://www.indiastudychannel.com/resources/37546-CUSAT-B-TECH-Degree-Course-Sem-VI-TOOL.aspx#%23http://www.indiastudychannel.com/resources/37546-CUSAT-B-TECH-Degree-Course-Sem-VI-TOOL.aspx#%23http://www.indiastudychannel.com/resources/37546-CUSAT-B-TECH-Degree-Course-Sem-VI-TOOL.aspx#%23 -
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Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least one
Buestion -rom each module and not more than t3o Buestions-rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er -our Buestions out o- si@E Thereshould be at least one Buestion -rom each module and not morethan t3o Buestions -rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions -rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L!* = Mana$ement In-ormation S)stems
Objectives To introduce the methods and the influence of the information systems in management
milieu
To enable the students to use M"- as an effective tool in management and decision making
Mod4%e I ")1 'o4!s(
Information Systems-functions of management-le,els of management-framework for
information systems-systems approach-systems concepts-systems and their
en,ironment-effects of systems approach in information systems design-using
systems approach in problem sol,ing - strategic uses of information technology0
Mod4%e II ")1 'o4!s(
Computer 1undamentals2 "elecommunication and &etworks - Communication2 /edia2
/odems Channels - 3A&2 /A& 4A& - &etwork "opologies2 Internet2 Intranet and
E%tranet0 4ireless technologies like 4i-1i2 5luetooth and 4i-/a%0
Mod4%e III ")0 'o4!s(
'inds of Information Systems - "ransaction !rocessing System 6"!S7 - 8ffice
Automation System 68AS7 - /anagement Information System 6/IS7 - Decision Support
System 6DSS7 and roup Decision Support System 6DSS7 - E%pert System 6ES7 -
E%ecuti,e Support System 6EIS or ESS70
Mod4%e I/ ")1 'o4!s(
Information systems planning - critical success factor - business system planning -
ends.means analysis - organi9ing the information systems plan - system analysis and
design - alternati,e application de,elopment approaches - organi9ation of data
processing - security and ethical issues of information systems0
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Re#e!en&e Boo-s#E Schultheis #0 /ary Summer2Management Information Systems!he
Manager"s #iew2 "ata /craw $ill0
%E 'enneth : 3audon2 :ane !03audon2Management Information Systems
Organization and !echnology2 !earson.!$I2;*.e2
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE#!I - :e$ularit) in the class
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least one
Buestion rom each module and not more than t3o Buestionsrom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marksCandidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not morethan t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er one
BuestionE
Maximum Total Marks, 6(
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CS!" L!+ = 7rtiicial eural et3orks
Objectives
To teach the fundamental building blocks of >eural networks and to promote their widespread usein the current day scientific research environment.
Mod4%e I ")1 'o4!s(Introduction A Historical de.elo2ment A ,iolo$ical net3orks A Com2arison A et3ork architecture A7cti.ation unction A Learnin$ methods A McCullo$h Pitts euron Model A architecture A Learnin$ rules AHebbian learnin$ rules A Perce2tron Learnin$ rule A Delta learnin$ rule A Com2etiti.e A 5ut star rule A,oltsman learnin$ A Memor) based learnin$
Mod4%e II ")1 'o4!s(9eedor3ard net3orks A Introduction A Sin$le la)er 2erce2tron architecture A Perce2tron al$orithm orse.eral in2ut classes A Perce2tron con.er$ence theorem A Multila)er 2erce2tron net3orks A
,ack2ro2a$ation net3orks A 1eneralised delta learnin$ rule A back2ro2a$ation rule A 7rchitecture andtrainin$ A Learnin$ in back2ro2o$ation A Local minima and $lobal minima A merits and demerits o back2ro2o$ation net3orks A :adial ,asis 9unction >:,9? et3orks A 7l$orithm or an :,9 3ith i@ed centres
A 7daline and Madaline net3orks
Mod4%e III ")+ 'o4!s(Counter 2ro2a$ation net3orks A Winner take-all learnin$ A out star learnin$ A Gohonen sel or$ani6in$net3ork A 9ull counter 2ro2a$ation net3orks A Trainin$ 2hases A 9or3ard onl) counter 2ro2a$ation net3ork
A Learnin$ 4ector 8uanti6er
Mod4%e I/ ")+ 'o4!s(7ssociati.e memor) A Continuous and Discrete Ho2ield net3orks A Ener$) anal)sis A Stora$e and retrie.alal$orithm A ,olt6man machine A ,idirectional 7ssociati.e memor) A 7da2ti.e :esonance Theor) net3orks
A 722lications o eural net3orks A Sol.in$ o2timi6ation 2roblems A Sol.in$ Linear EBuations A Sol.in$
Tra.ellin$ Salesman Problem A 722lications in Pattern :eco$nition/ Ima$e Processin$
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# S Shi.anandam/ S Sumati/ S Dee2a/"ntroduction to >eural >etworks using MAT#A3 Tata
Mc1ra3 Hill% M urada/"ntroduction to Artificial >eural >etworks 'rdedition aico Publishers
Re#e!en&e Boo-s
# Gishan Mehrotra/ Chelkuri G Mohan/ Sanja) :anka/Elements of Artificial >eural >etworksPenram International
% Simon Ha)kin/Artificial >eural >etwork Pearson Education& Laurene 9ausett/ 9undamentals o eural et3orks/ %ndedition/ Pearson Education
( , en$anara)ana/Artificial >eural >etworks Prentice Hall India
Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+! - Tests >minimum %?&! - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etc#! - :e$ularit) in the class
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Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least one
Buestion -rom each module and not more than t3o Buestions-rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er -our Buestions out o- si@E Thereshould be at least one Buestion -rom each module and not morethan t3o Buestions -rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions -rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L!' = Distributed S)stems
Objectives
To impart basic knowledge of the issues concerning distributed systems from both
software and hardware viewpoints.
Mod4%e I ")0 'o4!s(52eratin$ s)stem undamentals - distributed s)stem conce2ts and architectures - major desi$n issues -distributed com2utin$ en.ironments >DCE?
Mod4%e II ")+ 'o4!s(Concurrent 2rocesses and 2ro$rammin$ - threads and 2rocesses - client ser.er model - time ser.iceslan$ua$e mechanisms or s)nchroni6ation - concurrent 2ro$rammin$ lan$ua$es
Mod4%e III ")+ 'o4!s(Inter-2rocess communication and coordination - messa$e 2assin$ communication - reBuest/re2l)communication - transaction communication -name and director) ser.ices - distributed mutual e@clusion -
leader election
Mod4%e I/ ")+ 'o4!s(Distributed 2rocess schedulin$ - static 2rocess schedulin$ d)namic load sharin$ and balancin$ - distributed2rocess im2lementation - real-time schedulin$ - conce2ts o distributed ile s)stems - distributed sharedmemor) - distributed com2uter securit)
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# Cho3 : < ohnson T5istributed Dperating -ystems and Algorithms 7ddison Wesle)
Re#e!en&e Boo-s# Sinha PG5istributed Dperating -ystems $oncepts and 5esign PHI
% Tanenbaum S5istributed Dperating -ystems Pearson Education& Coulouris 1 Dollimore < Gindber$ T5istributed-ystems $oncepts and 5esign 7ddison
Wesle)( Sin$hal M < Shi.aratriAdvanced $oncepts in Dperating -ystems 5istributed 5atabases And
Multiprocessor Dperating -ystems Mc1ra3 Hill
Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+! - Tests >minimum %?&! - 7ssi$nments >minimum %? such as home 3ork 2roblem sol.in$ $rou2 discussions Bui6
literature sur.e) seminar term-2roject sot3are e@ercises etc#! - :e$ularit) in the class
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Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least one
Buestion -rom each module and not more than t3o Buestions-rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er -our Buestions out o- si@E Thereshould be at least one Buestion -rom each module and not morethan t3o Buestions -rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions -rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L!0 = 9u66) Lo$ic and 722lications
Objectives
To impart the basic concepts of fuBBy set theory.
To understand the applications of fuBBy logic in various fields.
Mod4%e I ")1 'o4!s(Cris2 sets and u66) sets A introduction A cris2 sets an o.er.ie3 A the notion o u66) sets A basic conce2tso u66) sets A classical lo$ic an o.er.ie3 A u66) lo$ic 52erations on u66) sets A u66) com2lement Au66) union A u66) intersection A combinations o o2erations A $eneral a$$re$ation o2erations
Mod4%e II ")1 'o4!s(9u66) relationsA cris2 and u66) relations A binar) relations A binar) relations on a sin$le setA eBui.alenceand similarit) relations A com2atibilit) or tolerance relations A orderin$s A membershi2 unctions A methodso $eneration A deu66iication methods
Mod4%e III ")+ 'o4!s(9u66) measuresA $eneral discussion A belie and 2lausibilit) measures A 2robabilit) measures A 2ossibilit)and necessit) measures A relationshi2s amon$ classes o u66) measures
Mod4%e I/ ")+ 'o4!s(9u66) Lo$ic and 722licationsA a22lications o u66) lo$ic A 9u66) Controllers >o.er.ie3 < an e@am2le? Au66) s)stems and neural net3orks A u66) eural net3orks 9u66) Clusterin$ A u66) 2attern reco$nition Au66) Ima$e Processin$ A u66) databases A u66) inormation retrie.al
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books
# 1 Glir and T7 9ol$erFuBBy sets @ncertainty and "nformation Prentice Hall o India #""0% T :ossFuBBy #ogic with Engineering applications Mc1ra3 Hill Int Ed
Re#e!en&e Boo-s# H immermanFuBBy set theory and its Applications 4thEd. Glu3er 7cademic Publishers
%!!#
% 1 Glir and ,uan FuBBy sets and fuBBy logic, Theory and Applications Prentice Hall oIndia #""'
& H$u)en and EWalkerA first course in FuBBy logic 0ndEd. Cha2man and Hall/C:C #"""( en and : Len$ariFuBBy #ogic, "ntelligence $ontrol and "nformation Pearson Education
Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+! - Tests >minimum %?&! - 7ssi$nments >minimum %? such as home 3ork 2roblem sol.in$ $rou2 discussions Bui6
literature sur.e) seminar term-2roject sot3are e@ercises etc
#! - :e$ularit) in the class
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CS!" L!" = S2eech and Lan$ua$e Processin$
Objectives
To teach the fundamental concepts in speech processing and natural language processing through
which human&computer dialog systems may be developed.
Mod4%e I ")+ 'o4!s(Introduction= Words :e$ular E@2ressions and 7utomata Words and Transducers -$rams Part-o-S2eechTa$$in$ Hidden Marko. and ma@imum Entro2) Models
Mod4%e II ")+ 'o4!s(S2eech= Phonetics S2eech S)nthesis 7utomatic S2eech :eco$nition S2eech :eco$nition = 7d.ancedTo2ics Com2utational Phonolo$)
Mod4%e III ")+ 'o4!s(S)nta@= 9ormal 1rammars o En$lish S)ntactic Parsin$ Statistical Parsin$ 9eatures and ;niicationLan$ua$e and Com2le@it)
Mod4%e I/ ")+ 'o4!s(Semantics and Pra$matics= The :e2resentation o Meanin$ Com2utational Semantics Le@ical SemanticsCom2utational Le@ical Semantics Com2utational Discourse 722lications = Inormation E@traction8uestion 7ns3erin$ and Summari6ation Dialo$ and Con.ersational 7$ents Machine Translation
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# Daniel urask) and ames H Martin -peech and #anguage *rocessing , An "ntroduction to
>atural #anguage *rocessing Com2utational Lin$uistics and S2eech :eco$nition >SecondEdition? Prentice Hall %!!"
Re#e!en&e Boo-s# CDMannin$ and H Schut6eFoundations of -tatistical >atural #anguage *rocessing MIT
Press London %!!#% ames 7llen>atural #anguage @nderstanding %ndEdn ,enjamin/Cummin$s Pub Co #""(
Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+! - Tests >minimum %?&! - 7ssi$nments >minimum %? such as home 3ork 2roblem sol.in$ $rou2 discussions Bui6
literature sur.e) seminar term-2roject sot3are e@ercises etc#! - :e$ularit) in the class
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Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least one
Buestion -rom each module and not more than t3o Buestions-rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er -our Buestions out o- si@E Thereshould be at least one Buestion -rom each module and not morethan t3o Buestions -rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions -rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L#! = 7d.anced To2ics in 52eratin$ S)stems
Objectives
To teach advanced concepts related to operating systems including various categories and the
complex algorithms in their management functions.
Mod4%e I ")1 'o4!s(Introduction A 9unctions A Desi$n a22roaches A T)2es o ad.anced o2eratin$ s)stems A S)nchroni6ation
mechanisms A conce2t o a 2rocess A threads A critical section 2roblems A s)nchroni6ation 2roblems
Mod4%e II ")1 'o4!s(7rchitecture A mutual e@eclusion A deadlock detection A resource mana$ement A ile s)stems A sharedmemor) A schedulin$ A ailure reco.er) A ault tolerance
Mod4%e III ")+ 'o4!s(Multi2rocessor s)stem architecture A intercommunication net3orks A cachin$ A h)2ercube architectures A
structure o multi2rocessor o2eratin$ s)stem A desi$n issues A threads A 2rocess s)nchroni6ation A 2rocessorschedulin$ A memor) mana$ement A reliabilit) A ault tolerance
Mod4%e I/ ")+ 'o4!s(Introduction to database o2eratin$ s)tesms and realtime o2eratin$ s)stems A concurrenc) control Adistribted database s)stems A concurrenc) control A distributed database s)stems A concurrenc) controlal$orithms A basic s)nchroni6ation 2rimiti.es A lock based A time stam2 based
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# Mukesh Sin$al/Advanced Topics in Dperating -ystems/ Tata Mc1ra3 Hill
Re#e!en&e Boo-s# utt 1/ Dperating -ystems G A Modern *erspective/ 7ddison Wesle)% Schilberschat6 < 1al.in/ Dperating -ystem $oncepts/ 7ddison Wesle)& Tanenbaum 7S/Modern Dperating -ystems/ Pearson Education
Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+! - Tests >minimum %?&! - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etc#! - :e$ularit) in the class
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b
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least one
Buestion -rom each module and not more than t3o Buestions
-rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er -our Buestions out o- si@E Thereshould be at least one Buestion -rom each module and not morethan t3o Buestions -rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions -rom each module 3ith choice to ans3er one
BuestionE
Maximum Total Marks, 6(
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CS!" L## = 7d.anced Database Desi$n
Objectives To impart knowledge on the advancements in database management systems. This covers ideas on
the latest methodologies such as ob:ect oriented distributed and deductive database systemsalong with comparisons and some case studies.
to enable the student to analyBe design and implement modern database systems especially for a
distributed environment..
Mod4%e I ")) 'o4!s(5.er.ie3 o relational database conce2t - object oriented database - o.er.ie3 o object oriented conce2ts -object deinition lan$ua$e - object Buer) lan$ua$es - object database conce2tional desi$n A 5bject relationaland e@tended relational s)stems
Mod4%e II ")+ 'o4!s(Distributed database conce2ts - data ra$mentation re2lication and allocation - t)2es o distributed databases)stem - Buer) 2rocess - concurrenc) control or distributed database - o.er.ie3 o client - ser.erarchitecture and its relationshi2 to distributed database
Mod4%e III ")+ 'o4!s(Deducti.e database - introduction to deduction database 2rolo$/datalo$ notation - inter2retation o rules -basic inerence mechanism or lo$ic 2ro$rams - datalo$ 2ro$rams and their e.aluation - deduction database
s)stems - data Warehousin$ and data minin$ - database on World Wide Web - multimedia database - mobiledatabase - $eo$ra2hic inormation s)stem - di$ital libraries
Mod4%e I/ ")* 'o4!s(5racle and microsot access - basic structure o the oracle s)stem - database structures and its mani2ulationin oracle - stora$e or$ani6ation 2ro$rammin$ oracle a22lications - oracle tools - an o.er.ie3 o Microsotaccess eatures and unctionalit) o access - distributed databases in oracle
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# Elmasri < a.atheFundamentals of 5atabase -ystems Pearson Education ourth edition
Re#e!en&e Boo-s# :amakrishnan : < 1ehrke 5atabase Management -ystems Mc1ra3 Hill% 5Kneil P < 5Kneil E5atabase *rinciples *rogramming And *erformance Harcourt 7sia
>Mor$an Gauman?& Silberschat6 Gorth H9 < Sudarshan S5atabase -ystem $oncepts Tata Mc1ra3 Hill
( Theor) T5atabase Modelling And 5esign Harcourt 7sia >Mor$an Gauman?
Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork 2roblem sol.in$ $rou2 discussions Bui6
literature sur.e) seminar term-2roject sot3are e@ercises etc
#!I - :e$ularit) in the class
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Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least one
Buestion -rom each module and not more than t3o Buestions-rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er -our Buestions out o- si@E Thereshould be at least one Buestion -rom each module and not morethan t3o Buestions -rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions -rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L#% = Di$ital Ima$e Processin$
Objectives
To impart the introductory concepts of image processing
To understand all the elements of image processing beginning from formation and digitiBation to
enhancement restoration edge detection segmentation and compression .
Mod4%e I ")* 'o4!s(Introduction - di$ital ima$e re2resentation - undamental ste2s in ima$e 2rocessin$ - elements o di$ital ima$e2rocessin$ s)stems - di$ital ima$e undamentals - elements o .isual 2erce2tion - a sim2le ima$e model - sam2lin$
and Buanti6ation - basic relationshi2 bet3een 2i@els - ima$e $eometr) - ima$e transorms - introduction to 9ouriertransorm - discrete 9ourier transorm >D9T? - 2ro2erties D9T- other se2arable ima$e transorms - Walsh Hadamardand Discrete Cosine transorms Hotellin$ transorm
Mod4%e II ")2 'o4!s(Ima$e enhancement - basic $re) le.el transormation - histo$ram eBuali6ation - ima$e subtraction - Ima$e a.era$in$ -s2atial ilterin$ - smoothin$ shar2enin$ ilters - La2lacian ilters Enhancement in the reBuenc) domain - reBuenc)domain ilters - smoothin$ shar2enin$ ilters - homomor2hic ilterin$
Mod4%e III ")2 'o4!s(Ima$e restoration - model o Ima$e de$radation/restoration 2rocess - noise models - in.erse ilterin$ - least meansBuare ilterin$ - constrained least mean sBuare ilterin$ Ed$e detection - thresholdin$ - re$ion based se$mentation -,oundar) re2resentation
Mod4%e I/ ")+ 'o4!s(
Ima$e com2ression - undamental conce2ts o ima$e com2ression - com2ression models - inormation theoretic2ers2ecti.e Lossless com2ression - Human codin$ - arithmetic codin$ - bit 2lane codin$ - run len$th codin$ Loss)com2ression - transorm codin$ - Ima$e com2ression standards
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# :C 1on6ale6 and :E Woods5igital "mage *rocessing & 0nded. Prentice Hall o India e3
Delhi
Re#e!en&e Boo-s# , Chanda and DD Majumder5igital "mage *rocessing and Analysis PHI
% 7G ainFundamentals of 5igital "mage *rocessing PHI& WG Pratt5igital "mage *rocessing ohn Wile) %!!+( M Sonka 4 Hla.ac and : ,o)le"mage *rocessing Analysis and Machine 7ision
,rooks/colic Thom2son Learnin$ #"""
Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+! - Tests >minimum %?&! - 7ssi$nments >minimum %? such as home 3ork 2roblem sol.in$ $rou2 discussions Bui6
literature sur.e) seminar term-2roject sot3are e@ercises etc
#! - :e$ularit) in the class
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Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least one
Buestion -rom each module and not more than t3o Buestions-rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er -our Buestions out o- si@E Thereshould be at least one Buestion -rom each module and not morethan t3o Buestions -rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions -rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L#& = 4LSI Desi$n
Objectives
To impart the required skills to the students in design of 7#-" components.
Mod4%e I ")1 'o4!s(Introduction to M5S technolo$) - IC technolo$) - M5S and 4LSI - M5S and QCM5S abrication -thermal as2ects - M5S circuits tub ties and latch u2 - 3ire 2arasitic - desi$n rules and la)outs - multila)erCM5S 2rocess - la)out dia$rams - stick dia$rams - hierarchical stick dia$rams - la)out desi$n anal)sis
tools
Mod4%e II ")1 'o4!s(Lo$ic $ates - re.ie3 o combinational lo$ic circuits - basic $ate la)outs A dela) - 2o3er Consum2tion -s2eed 2o3er 2roduct - 3ires and dela) A combinational lo$ic net3orks - la)out desi$n methods -net3ork
dela) - cross talk A 2o3er o2timi6ation - s3itch lo$ic net3orks
Mod4%e III ")2 'o4!s(SeBuential machines - latches and li2 lo2s - seBuential s)stem desi$n -subs)stem desi$n - 2i2elinin$ - data2aths - adders - 7L; - :5M - :7M -9P17 - PL7 A multi2liers
Mod4%e I/ ")2 'o4!s(9loor 2lannin$ - methods - loor 2lan o a ( bit 2rocessor - o chi2 connections Aarchitecture desi$n -re$ister transer desi$n - architecture or lo3 2o3er - architecture testin$ - cad s)stems and al$orithms -simulation - la)out s)nthesis
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# eil H E Weste/ Gamran Eshra$hian/*rinciples of $MD- 7#-" 5esign/ 7ddison Wesle)
Re#e!en&e Boo-s
# C Puck ell D 7 < Eshra$hian G/ 3asic 7#-" 5esign & -ystems and $ircuits% Mead C/ Con3a) L/"ntroduction to 7#-" -ystem/ 7ddison Wesle)
& Wa)ne Wol/Modern 7#-" 5esign/ Phi2e
Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+! - Tests >minimum %?
&! - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etc
#! - :e$ularit) in the class
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CS!" L#( = Inormation Theor) and Codin$
Objectives
To teach the fundamentals of information quality error control in communication process
and various systems of coding information for reliable communications.
Mod4%e I ")1 'o4!s(Inormation theor) - inormation and entro2) - 2ro2erties o entro2) o a binar) memor) less source -e@tension o a discrete memor) less source -source codin$ theorem - Shannon-9ano codin$ - Human codin$- Lem2el i. codin$ - discrete memor) less source - binar) s)mmetric channel - mutual inormation -2ro2erties - channel ca2acit) - channel codin$ theorem -inormation ca2acit) theorem
Mod4%e II ")1 'o4!s(Codin$ - linear block codes - $enerator matrices - 2arit) check matrices - encoder-s)ndrome and errordetection - minimum distance - error correction and error detection ca2abilities - c)clic codes - codin$ anddecodin$
Mod4%e III ")+ 'o4!s(Introduction to al$ebra - $rou2s - ields - binar) ield arithmetic - construction o $alois ield - basic 2ro2erties- com2utations - .ector s2aces - matrices - ,CH codes - descri2tion - decodin$ - reed **eneral codes
Mod4%e I/ ")+ 'o4!s(Codin$ - con.olutional codes - encoder - $enerator matri@ - transorm domain re2resentation - state dia$ram- distance 2ro2erties - ma@imum likelihood decodin$ - 4iterbi decodin$ - seBuential decodin$ - interlea.edcon.olutional codes
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books
# Simon Ha)kin/ $ommunication -ystems/ ohn Wile)% Shu Lin < Costello D/Error $ontrol $oding & Fundamentals and Applications/ Prentice Hall
Inc En$le3ood Clis
Re#e!en&e Boo-s
# C Das / Malik SG < Chatterje PG/*rinciples of 5igital $ommunication/ e3 7$eInternational Limited
% Sam Shanmu$ham/5igital and Analog $ommunications/ ohn Wile)& Simon Ha)kin/5igital $ommunications/ ohn Wile)( Taub < Shillin$/*rinciples of $ommunication -ystems/ Tata Mc1ra3 Hill
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE#!I - :e$ularit) in the class
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least oneBuestion rom each module and not more than t3o Buestions
rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not morethan t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L#* = Multimedia
Objectives
To impart the fundamental concepts of multimedia.
Mod4%e I ")+ 'o4!s(Multimedia s)stem or$ani6ation and architecture - 85S architecture - multimedia distributed 2rocessin$ models -multimedia conerencin$ model - stora$e or$ani6ation
Mod4%e II ")+ 'o4!s(Ps)choacoustics - di$ital audio and com2uter - di$ital re2resentation o sound - audio si$nal 2rocessin$ >editin$ andsam2lin$? - audio 2roduction - di$ital music - musical instrument s)nthesi6er - MIDI 2rotocol
Mod4%e III ")+ 'o4!s(
:aster scannin$ 2rinci2le - color undamental - color .ideo 2erormance measurement - analo$ audio - stereo eect -MPE1 and D4I technolo$) - multimedia a22lications - toolkit and h)2er a22lication
Mod4%e I/ ")+ 'o4!s(
Multimedia inormation s)stem - o2eratin$ s)stem su22ort middle3are s)stem ser.ice architecture -
2resentation ser.ices - user interace - ile s)stem and inormation and inormation model - 2resentation and
anchorin$ ile - Multimedia standards - role o standards - standardi6ation issues - distributed multimedias)stems
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books
# P G ,uord/Multimedia -ystems/ 7WL
Re#e!en&e Boo-s
# WI 1rosk)/ : ain and : Mehrotra/ The
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Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least one
Buestion -rom each module and not more than t3o Buestions-rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er -our Buestions out o- si@E Thereshould be at least one Buestion -rom each module and not morethan t3o Buestions -rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions -rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L#+ = Web Pro$rammin$
Objectives
To teach the various technologies available for programming the web applications.
Mod4%e I ")1 'o4!s(Introduction to Web 2ro$rammin$ A Introduction to S1ML -eatures A HTML NHTML DHTML NML AHTML 4s NML A Creatin$ NML documents A Parsin$ an NML document A Writin$ 3ell -ormed documents
A 5r$ani6in$ elements 3ith names2aces A De-inin$ elements in a DTD A Declarin$ elements and attributesin a DTD
Mod4%e II ")1 'o4!s(C1I/Perl= Creatin$ link to a C1I Scri2t A ;sin$ a link to send data to a C1I Scri2t A 2arsin$ data sent to a
Perl C1I scri2t A ;sin$ C1I scri2t to 2rocess -orm data A ;sin$ scalar .ariables in Perl A ;sin$ .ariables inPerl A ;sin$ arithmetic o2erators in Perl A 7ssociatin$ a -orm 3ith a scri2t
Mod4%e III ")+ 'o4!s(E.ent dri.en 2ro$rammin$ usin$ a.a a22lets A a.a Ser.er Pa$es A SP scri2tin$ elements A Linkin$ toe@ternal -iles A SP declarations A SP E@2ressions A SP Scri2lets A Processin$ client reBuests A a.a ,eans= -eatures A desi$nin$ a.a ,eans A Pro2erties o- beans A creation o- e.ents A E, basics A t)2es o- beans Ade.elo2ment o- session beans A ste2s in creation and im2lementin$ inter-aces A 7ccessin$ a database -romSP
Mod4%e I/ ")+ 'o4!s(
PHP = De-inin$ PHP .ariables A .ariable t)2es A o2erators A control -lo3 constructs in PHP A Establishin$connection 3ith M)S8L database A mana$in$ s)stem data A 2arsin$ data bet3een 2a$es A Introduction to77N 2ro$rammin$
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# :obert W Sebesta*rogramming with Corld Cide Ceb (thedition Pearson Education %!!"
Re#e!en&e Boo-s
# Nue ,al et al The Ceb Carrior 8uide to Ceb programming Thomson Learnin$% Chris ,ates Ceb *rogramming , 3uilding "nternet Applications 'rded Wile) 7cademic
Catalo$
& HM Deitel P Deitel 7, 1oldber$"nternet and Corld Cide Ceb ,
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE#!I - :e$ularit) in the class
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least oneBuestion rom each module and not more than t3o Buestions
rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not morethan t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L#' = 1ra2h Theor) and Combinatorics
Objectives
To introduce the basics of graph theory as a modelling and analysis tool in computer science and
engineering. To introduce the structures such as graphs and trees and several combinatorial techniques which
are needed in number theory based computing and network security studies in $omputer -cience.
Mod4%e I ")+ 'o4!s(Introduction to $ra2hs - deinitions - sub$ra2hs - 2aths and c)cles - matri@ re2resentation o $ra2hs - Euler
tours - Chinese 2ostman 2roblem - 2lanar $ra2hs -EulerKs ormula - 2latonic bodies - a22lications oGurato3skiKs theorem - Hamiltonian $ra2hs - $ra2h colourin$ and chromatic 2ol)nomials - ma2 colourin$
Mod4%e II ")1 'o4!s(Trees - deinitions and 2ro2erties - rooted trees - trees and sortin$ - 3ei$hted trees and 2rei@ codes -biconnected com2onents and articulation 2oints - the ma@-lo3 min-cut theorem - ma@imum bi2artitematchin$ - Matchin$s -matchin$s and au$mentin$ 2aths -the 2ersonal assi$nment 2roblem A et3orks -lo3s and cuts - ord and 9ulkerson al$orithm - se2aratin$ sets
Mod4%e III ")) 'o4!s(9undamental 2rinci2les o countin$ - 2ermutations and combinations - binomial theorem - combinations3ith re2etition - combinatorial numbers - 2rinci2le o inclusion and e@clusion - deran$ements -arran$ements 3ith orbidden 2ositions
Mod4%e I/ ")1 'o4!s(
1eneratin$ unctions - 2artitions o inte$ers - the e@2onential $eneratin$ unction - the summation o2erator -recurrence relations - irst order and second order - non-homo$eneous recurrence relations - method o$eneratin$ unctions
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books
# 1rimaldi :P/5iscrete and $ombinatorial Mathematics, An Applied "ntroduction/ 7ddisonWesle)
% Clark < Holton D 7/A First #ook at 8raph Theory/ 7llied Publishers>World Scientiic?
Re#e!en&e Boo-s
# Corman TH/ Leiserson CE < :i.est :L/"ntroduction to Algorithms/Prentice Hall India
% Mott L/ Gandel 7 < ,aker TP/5iscrete Mathematics for $omputer-cientists And Mathematicians/ Prentice Hall o India
& Liu CL/Elements of 5iscrete Mathematics/ Mc1ra3 Hill( :osen GH 5iscrete Mathematics and "ts A lications Mc1ra3 Hill
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE#!I - :e$ularit) in the class
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least oneBuestion rom each module and not more than t3o Buestionsrom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marksCandidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not morethan t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L#0 = Machine Learnin$
Objectives
To teach the fundamental concepts of Machine #earning
To equip the learners with techniques and methods using which machines mimic the human
learning process.
Mod4%e I ")0 'o4!s(Preliminaries - Introduction - Learnin$ In2ut-5ut2ut 9unctions - Learnin$ and ,ias - Sam2le a22lications -,oolean 9unctions - :e2resentation - Classes o ,oolean 9unctions - Introduction to eural et3orks
Mod4%e II ")1 'o4!s(;sin$ 4ersion S2aces or Learnin$ - 4ersion S2aces and Mistake ,ounds - 4ersion 1ra2hs - Learnin$ asSearch o a 4ersion S2ace - The Candidate Elimination Method - eural et3orks - Threshold Lo$ic ;nits -Linear Machines - et3orks o TL;s - Trainin$ 9eedor3ard et3orks b) ,ack2ro2o$ation - S)ner$ies,et3een eural et3ork and Gno3led$e-,ased Methods - Statistical Learnin$ - ;sin$ Statistical DecisionTheor) - Learnin$ ,elie et3orks - ei$hest-ei$hbor Methods
Mod4%e III ")1 'o4!s(Decision Trees - Deinitions - Su2er.ised Learnin$ o ;ni.ariate Decision Trees - et3orks EBui.alent toDecision Trees - 5.erittin$ and E.aluation - The Problem o :e2licated Subtrees - The 2roblem o Missin$7ttributes - Com2arisions - Inducti.e Lo$ic Pro$rammin$ - otations and Deinitions - 7 1eneric ILP7l$orithm - Inducin$ :ecursi.e Pro$rams - Choosin$ Literals to 7dd - :elationshi2 ,et3een ILP andDecision Tree Induction - Com2utational Learnin$ Theor) - otation and 7ssum2tions or P7C Learnin$Theor) - P7C Learnin$ - The 4a2nik-Cher.onenkis Dimension - 4C Dimension and P7C Learnin$
Mod4%e I/ ")1 'o4!s(;nsu2er.ised Learnin$ - Clusterin$ Methods - Hierarchical Clusterin$ Methods - Tem2oral-Dierence
Learnin$ - Tem2oral Patterns and Prediction Problems - Su2er.ised and Tem2oral-Dierence Methods -Incremental com2utation o the >delta 3?i - 7n e@2eriment 3ith TD Methods - Theoretical :esults - Intra-SeBuence Wei$ht ;2datin$ - Dela)ed-:einorcement Learnin$ - The 1eneral Problem - Tem2oralDiscountin$ and 52timal Policies - 8-Learnin$ - Discussion/ Limitations/ and E@tensions o 8-Learnin$ -E@2lanation-,ased Learnin$ - Deducti.e Learnin$ - Domain Theories - E.aluable Predicates - More1eneral Proos - ;tilit) o E,L - 722lications
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books
# Ethem Alpayd@n2 Introduction to Machine $earning %&daptive
Computation and Machine $earning'2 /I" !ress2
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?
&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE
#!I - :e$ularit) in the class
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least oneBuestion rom each module and not more than t3o Buestionsrom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not more
than t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L#" = Sot Com2utin$
Objectives
To introduce the ideas of fuBBy sets fuBBy logic and use of heuristics based on human experience.
To become familiar with neural networks that can learn from available examples and generaliBe
to form appropriate rules for inferencing systems.
To provide the mathematical background for carrying out the optimiBation associated with neural
network learning. To familiariBe with genetic algorithms and other random search procedures useful while seeking
global optimum in self&learning situations . To introduce case studies utiliBing the above and illustrate the intelligent behavior of programs
based on soft computing.
Mod4%e I ")1 'o4!s(Introduction to 1enetic 7l$orithm/ 1enetic 52erators and Parameters/ 1enetic 7l$orithms in Problem
Sol.in$/ Theoretical 9oundations o 1enetic 7l$orithms/ Im2lementation Issues - s)stems
Mod4%e II ")1 'o4!s(eural Model and et3ork 7rchitectures/ Perce2tron Learnin$/ Su2er.ised Hebbian Learnin$/,ack2ro2a$ation/ 7ssociati.e Learnin$/ Com2etiti.e et3orks/ Ho2ield et3ork/ Com2utin$ 3ith euralets and a22lications o eural et3ork
Mod4%e III ")+ 'o4!s(Introduction to 9u66) Sets/ 52erations on 9u66) sets/ 9u66) :elations/ 9u66) Measures/ 722lications o9u66) Set Theor) to dierent branches o Science and En$ineerin$
Mod4%e I/ ")+ 'o4!s(7d.anced To2ics= Su22ort 4ector Machines/ E.olutionar) com2utation >EC?- E.olutionar) al$orithms/Harmon) search/ S3arm intelli$ence
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# S:an$/ CTSun and EMi6utani/>euro&FuBBy and -oft $omputing/ Pearson Education/
%!!(
Re#e!en&e Boo-s# M Mitchell/An "ntroduction to 8enetic Algorithms/ Prentice-Hall/ #""0
% D E 1oldber$/ 8enetic Algorithms in -earch DptimiBation and Machine #earning/ 7ddison-Wesle)/ #"0"
& S 4 Gartalo2oulos/ @nderstanding >eural >etworks and FuBBy #ogic, 3asic $oncepts and
Applications/ IEEE Press - PHI/ %!!(( S :ajasekaran < 1 7 4ija)alakshmi Pai/>eural >etworks FuBBy #ogic and 8enetic
Al orithms, - nthesis ; A lications PHI %!!&
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE
#!I - :e$ularit) in the class
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least oneBuestion rom each module and not more than t3o Buestionsrom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not morethan t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L%! = Inormation :etrei.al
Objectives To familiariBe the students with tools and techniques for deriving the right information at the
right time in the current scenario of information explosion
To present the techniques for storage of many forms of information such as text image audio and
video formats and to present several issues related to different "+ tasks.
Mod4%e I ")0 'o4!s(Introduction= Inormation .ersus Data :etrie.al/ I:= Past/ 2resent/ and uture ,asic conce2ts= The retrie.al2rocess/ lo$ical .ie3 o documents Modelin$= 7 Ta@onom) o I: models/ ad-hoc retrie.al and ilterin$Classic I: models= Set theoretic/ al$ebraic/ 2robabilistic I: models/ models or bro3sin$
Mod4%e II ")2 'o4!s(:etrie.al e.aluation= Perormance e.aluation o I:= :ecall and Precision/ other measures/ :eerenceCollections/ such as T:EC/ C7CM/ and ISI data sets 8uer) Lan$ua$es= Ge)3ord based Bueries/ sin$le3ord Bueries/ conte@t Bueries/ ,oolean 8ueries/ 8uer) 2rotocols/ Buer) o2erations
Mod4%e III ")2 'o4!s(Te@t and Multimedia Lan$ua$es and 2ro2erties/ Metadata/ Te@t ormats/ Marku2 lan$ua$es/ Multimedia
data ormats/ Te@t 52erations Inde@in$ and searchin$= In.erted iles/ Sui@ trees/ Sui@ arra)s/ si$natureiles/ seBuential searchin$/ Pattern matchin$
Mod4%e I/ "). 'o4!s(Multimedia I:= S2atial access methods/ 1eneric multimedia Inde@in$ a22roach/ Distance unctions/ eaturee@traction/ Ima$e eatures and distance unctions Searchin$ the Web= Characteri6in$ and measurin$ theWeb Search En$ines= Centrali6ed and Distributed architectures/ user Interaces/ :ankin$/ Cra3lin$ theWeb/ Web directories/ D)namic search and Sot3are 7$ents
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Book# : ,ae6a-ates and , : eto/Modern "nformation +etrieval/ Pearson Education/ %!!(Re#e!en&e Boo-s# C .an :ijsber$en/"nformation +etrieval/ ,utter3orths/ #"'"% ::Gorha$e/ Inormation Stora$e and :etrie.al/ Wile) Student Edn/ %!!+
& CD Mannin$ and H Schut6e/Foundations of -tatistical natural #anguage *rocessing
>Cha2ters #&/ #(/ and #* onl)?/ The MIT Press/ Cambrid$e/ London%!!#( D Hand/ H Mannila/ P Sm)th/5ata Mining/ Prentice Hall o India/ %!!(
Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+! - Tests >minimum %?&! - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etc
#! - :e$ularit) in the class
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Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least oneBuestion -rom each module and not more than t3o Buestions-rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er -our Buestions out o- si@E Thereshould be at least one Buestion -rom each module and not morethan t3o Buestions -rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions -rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L%# = Di$ital Desi$n usin$ 4HDL
Objectives
To teach the various aspects in the design of digital circuits using 71ated? 9li2-lo2 - 5ther9li2-lo2 t)2es - PLD Primiti.e memor) elements - Timin$ reBuirements and S)nchronous in2ut data -Multibit latches and re$isters - shit re$isters - Shit re$ister counters - Counters - Detectin$ non-clock si$naled$es A Memories - 9inite state machines - 9SM state dia$rams - Three 2rocess 9SM 4HDL tem2late - Statedia$ram de.elo2ment - State encodin$ and state assi$nment - su22osedl) state 9SMs - Counters as Moore9SMs - 7l$orithmic State Machine charts 7SM charts to 4HDL - S)stem architecture - Successi.ea22ro@imation re$ister desi$n e@am2le - SeBuential Multi2lier Desi$n - Sub2ro$rams - 9unctions -
Procedures - 7rra) attributes and unconstrained arra)s A 5.erloadin$ Sub2ro$rams and o2erators A T)2econ.ersions
Mod4%e I/ ")+ 'o4!s(Packa$es and 2acka$e bodies - Standard and De actor standard 2acka$es - Packa$es or 4HDL te@t out2ut-Sim2le seBuential test benches - S)stems clock - S)stem reset - S)nchroni6in$ stimulus $eneration andmonitorin$ A Test bench or successi.e a22ro@imation re$ister - 5ut2ut .eriication in stimulus 2rocedures -,us unctional models A :es2onse monitors - Modular desi$n 2artitionin$ and hierarch) - Desi$n units and
librar) units - Desi$n libraries - Direct desi$n entit) instantiation - Coni$uration declarations - Com2onentconnections - Parameteri6ed desi$n entities - Librar) o 2arameteri6ed modules >LPM? - 1enerate statement
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# Peter 7shenden The 5esigner?s 8uide to 7
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE#!I - :e$ularit) in the class
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least one
Buestion rom each module and not more than t3o Buestionsrom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not morethan t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er one
BuestionE
Maximum Total Marks, 6(
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CS!" L%% = Com2utational 1eometr)
Objectives
To teach the al$orithms concerned 3ith $eometric sha2es and i$ures/ 2articularl) related to s2acemani2ulationE
Mod4%e I ")+ 'o4!s(Introduction - 7n e@am2le = con.e@ hull - de$eneracies and robustness - a22lication domains - line se$mentintersection - the doubl)-connected ed$e list - com2utin$ the o.erla) o t3o subdi.isions - booleano2erations - $uardin$ and 2ol)$on trian$ulations - 2artitionin$ a 2ol)$on into monotone 2ieces -trian$ulatin$ a monotone 2ol)$on - Linear 2ro$rammin$ - the $eometr) o castin$ - hal-2lane intersection -
incremental linear 2ro$rammin$ - randomi6ed linear 2ro$rammin$ - unbounded linear 2ro$rams - linear2ro$rammin$ in hi$her dimensions - smallest enclosin$ discs
Mod4%e II ")+ 'o4!s(
ortho$onal ran$e searchin$ - #-dimensional ran$e searchin$ - Gd-Trees - ran$e trees - hi$her dimensionalran$e trees - $eneral sets o 2oints - ractional cascadin$ - 2oint location and tra2e6oidal ma2s - arandomi6ed incremental al$orithm - dealin$ 3ith de$enerate cases - a tail estimate - .oronoi dia$rams -com2utin$ the .oronoi dia$ram - .oronoi dia$rams o line se$ments - arthese-2oint .oronoi dia$ramsarran$ements and dualit) - com2utin$ the discre2anc) - dualit) - arran$ements o lines - le.els anddiscre2anc)
Mod4%e III ")+ 'o4!s(Delauna) trian$ulations - trian$ulations o 2lanar 2oint sets - com2utin$ the delauna) trian$ulation - theanal)sis - a rame3ork o randomi6ed al$orithms - $eometric data structures - inter.al trees - 2riorit) searchtrees - se$ment trees - con.e@ hulls - com2le@it) in &-s2ace - com2utin$ con.e@ hulls in &-s2ace - anal)sis -con.e@ hulls and hal-s2ace intersection - binar) s2ace 2artitions - determination o ,SP trees - ,SP treesand the 2ainterKs al$orithm - construction o ,SP tree - the si6e o ,SP tree in &-s2ace - ,SP trees or lo3-densit) scenes
Mod4%e I/ ")+ 'o4!s(robot motion 2lannin$ - 3ork s2ace and coni$uration s2ace - a 2oint robot - minko3ski sums -translational motion 2lannin$ - motion 2lannin$ 3ith rotations - Buadtrees >non-uniorm mesh $eneration? -uniorm and non-uniorm meshes - Buadtrees or 2oint sets - rom Buadtrees to meshes - .isibilit) $ra2hs -shortest 2aths or a 2oint robot - com2utin$ the .isibilit) $ra2h - shortest 2aths or a translatin$ 2ol)$onalrobot - sim2le@ ran$e searchin$ - 2artition trees - multi-le.el 2artition trees - cuttin$ trees
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books
#E Mark de ,er$/ Mark .an Gre.eld/ Mark 5.ermars/ 5tried Sch3art6ko2/$omputational 8eometry , Algorithms and Applications/ S2rin$er/ e3 ork/ #""'E
Re#e!en&e Boo-s
#E 9ranco Pre2arata and Michael IE Shamos/ $omputational 8eometry , an "ntroduction
S2rin$er/ e3 ork/ #"0*E
%E Hean-Daniel ,oissonnat and Mariette .inec/Algorithmic 8eometry/ Cambrid$e;ni.ersit) Press/ #""0E
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE#!I - :e$ularit) in the class
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least oneBuestion rom each module and not more than t3o Buestions
rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not morethan t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L%& = Simulation and Modellin$
Objectives
To teach the students how to reproduce real&world events or process under controlled
laboratory conditions using mainly mathematical models.
Mod4%e I ")0 'o4!s(Introduction - s)stems and models - com2uter simulation and its a22lications -continuous s)stem simulation- modelin$ continuous s)stems - simulation o continuous s)stems - discrete s)stem simulation -methodolo$) A e.ent schedulin$ and 2rocess interaction a22roaches - random number $eneration -testin$ orandomness - $eneration o stochastic .ariates - random sam2les rom continuous distributions - uniormdistribution - e@2onential distribution m-Erlan$ distribution - $amma distribution - normal distribution - betadistribution - random sam2les rom discrete distributions - ,ernoulli - discrete uniorm -binomial -$eometric and 2oisson
Mod4%e II ")2 'o4!s(E.aluation o simulation e@2eriments - .eriication and .alidation o simulation e@2eriments - statistical
reliabilit) in e.aluatin$ simulation e@2eriments -conidence inter.als or terminatin$ simulation runs -simulation lan$ua$es -2ro$rammin$ considerations - $eneral eatures o 1PSS - SIM SC:IPT andSIM;L7
Mod4%e III ")* 'o4!s(Simulation o Bueuein$ s)stems - 2arameters o Bueue - ormulation o Bueuein$ 2roblems - $eneration oarri.al 2attern - $eneration o ser.ice 2atterns -Simulation o sin$le ser.er Bueues - simulation o multi-ser.er Bueues -simulation o tandom Bueues
Mod4%e I/ ")* 'o4!s(Simulation o stochastic net3ork - simulation o PE:T net3ork - deinition o net3ork dia$rams - or3ard2ass com2utation - simulation o or3ard 2ass -back3ard 2ass com2utations - simulation o back3ard 2ass -determination o loat and slack times determination o critical 2ath - simulation o com2lete net3ork -merits o simulation o stochastic net3orks
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Re#e!en&e Boo-s# C Deo / -ystem -imulation And 5igital $omputer/ Prentice Hall o India% 1ordan 1/ -ystem -imulation/ Prentice Hall o India& La3 7M < Getton WD/ -imulation Modelling and Analysis/ Mc1ra3 Hill
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE#!I - :e$ularit) in the class
Noe5 5ne o the assi$nments shall be com2uter based simulation o continuous s)stems usin$an) technical com2utin$ sot3are
5ne o the tests must be com2uter based >2ractical?E
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least one
Buestion rom each module and not more than t3o Buestions
rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not morethan t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er one
BuestionE
Maximum Total Marks, 6(
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CS!" L%( = Com2uter ,ased umerical Methods
Objectives
To impart the basic concepts of mathematical modelling of problems in science and engineering and to
know procedures for solving different kinds of problems. To understand the various numerical techniques which provide solutions to non linear equations
partial differential equations etc that describe the mathematical models of problems.
Mod4%e I ")+ 'o4!s(Errors in numerical com2utation - mathematical 2reliminaries - errors and their anal)sis - machine com2utations -
com2uter sot3are 7l$ebraic and Transcendental EBuations - bisection method - iteration method - method o alse2osition - rate o con.er$ence - method or com2le@ root - MullerFs method - Buotient dierence method - e3ton-:a2hson method
Mod4%e II ")+ 'o4!s(Inter2olation A introduction - errors in 2ol)nomial inter2olation - inite dierences - decision o errors - e3tonFsormula or inter2olation 1auss Sterlin$ ,esselFs E.erettFs 9ormula - inter2olation b) une.enl) s2aced 2oints -La$ran$e inter2olation ormula - di.ided dierence - e3tonFs $eneral inter2olation ormula
Mod4%e III ")+ 'o4!s(umerical Inte$ration and Dierentiation A introduction - numerical dierentiation - numerical inte$ration -tra2e6oidal rule - Sim2son #/& rule - Sim2son &/0 rule - ,ooleFs and WeddleFs rules - Euler-Maclariaun ormula -1aussian ormula - numerical e.aluation o sin$ular inte$rals
Mod4%e I/ ")+ 'o4!s(
Statistical Com2utations -reBuenc) Chart - method o least sBuare cur.e ittin$ 2rocedures - ittin$ a strai$ht line -cur.e ittin$ b) sum o e@2onential - data ittin$ 3ith cubic s2lines - a22ro@imation o unctions :e$ression 7nal)sis- linear and nonlinear re$ression - multi2le re$ression - statistical Bualit) control methods
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# E ,ala$urusam)>umerical Methods Tata Mc1ra3-Hill PubCoLtd e3 Delhi #"""% C9 1erald and P5 Wheatle) Applied >umerical Analysis th Ed. Pearson Education 7sia
e3 Delhi %!!%
Re#e!en&e Boo-s# P Gandasam) G Thila$a.ath) and G 1una.ath)>umerical Methods SChand Co Ltd e3
Delhi %!!&% :L ,urden and TD 9aires>umerical Analysis 6thEd Thomson 7sia P.t Ltd Sin$a2ore
%!!%& Shastri "ntroductory methods of numerical analysis Prentice Hall International( 4 :a araman "ntroduction to >umerical Methods Tata Mc1ra3 Hill
Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+! - Tests >minimum %?
&! - 7ssi$nments >minimum %? such as home 3ork 2roblem sol.in$ $rou2 discussions Bui6literature sur.e) seminar term-2roject sot3are e@ercises etc
#! - :e$ularit) in the class
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Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least one
Buestion -rom each module and not more than t3o Buestions-rom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er -our Buestions out o- si@E Thereshould be at least one Buestion -rom each module and not morethan t3o Buestions -rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions -rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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CS!" L%* = Pattern :eco$nition
Objectives
To impart a basic knowledge on pattern recognition and to give a sound idea on the topics of
parameter estimation and supervised learning linear discriminant functions and syntacticapproach to *+.
To provide a strong foundation to students to understand and design pattern recognition systems.
Mod4%e I ")2 'o4!s(Introduction - introduction to statistical - s)ntactic and descri2ti.e a22roaches - eatures and eaturee@traction - learnin$ - ,a)es Decision theor) - introduction - continuous case - %-cate$or) classiication -minimum error rate classiication - classiiers - discriminant unctions - and decision suraces - error
2robabilities and inte$rals - normal densit) - discriminant unctions or normal densit)
Mod4%e II ")2 'o4!s(Parameter estimation and su2er.ised learnin$ - ma@imum likelihood estimation - the ,a)es classiier -learnin$ the mean o a normal densit) - $eneral ,a)esian learnin$ - non2arametric technic - densit)estimation - 2ar6en 3indo3s - k-nearest nei$hbour estimation - estimation o 2osterior 2robabilities -nearest-nei$hbour rule - k-nearest nei$hbour rule
Mod4%e III ")2 'o4!s(Linear discriminant unctions - linear discriminant unctions and decision suraces - $eneralised linear
discriminant unctions - %-cate$or) linearl) se2arable case - non-se2arable beha.iour - linear 2ro$rammin$2rocedures - clusterin$ - data descri2tion and clusterin$ - similarit) measures - criterion unctions orclusterin$
Mod4%e I/ "). 'o4!s(S)ntactic a22roach to P: - introduction to 2attern $rammars and lan$ua$es - hi$her dimensional $rammars -tree/ $ra2h/ 3eb/ 2le@/ and sha2e $rammars - stochastic $rammars - attribute $rammars - 2arsin$ techniBues- $rammatical inerence
Te$&'in8 s&'eme C!edis5(& hours lecture and # hour tutorial 2er 3eek
Text Books# Duda < Hart PE/*attern $lassification And -cene Analysis/ ohn Wile)% 1on6ale6 :C < Thomson M1/ -yntactic *attern +ecognition & An "ntroduction/ 7ddison
Wesle)
Re#e!en&e Boo-s# 9u GS/ -yntactic *attern +ecognition And Applications/ Prentice Hall/ Ea$le3ood clis
% :ajjan Shin$hal/*attern +ecognition, Techniques and Applications/ 5@ord ;ni.ersit) Press/%!!0
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Ine!n$% Conin4o4s Assessmen %Maximum Marks&'()
+!I - Tests >minimum %?&!I - 7ssi$nments >minimum %? such as home 3ork/ 2roblem sol.in$/ $rou2 discussions/ Bui6/
literature sur.e)/ seminar/ term-2roject/ sot3are e@ercises/ etcE#!I - :e$ularit) in the class
Uni2e!si: E6$min$ion ;$e!n
*A+T A, -hort answer questions %one.two sentences) / x 0 marks12( marks
7ll Buestions are com2ulsor)E There should be at least oneBuestion rom each module and not more than t3o Buestionsrom an) moduleE
*A+T 3, Analytical.*roblem solving questions 4 x / marks10( marks
Candidates ha.e to ans3er our Buestions out o si@E Thereshould be at least one Buestion rom each module and not more
than t3o Buestions rom an) moduleE
*A+T $, 5escriptive.Analytical.*roblem solving questions 4 x 2( marks14( marks
T3o Buestions rom each module 3ith choice to ans3er oneBuestionE
Maximum Total Marks, 6(
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EE09 72+ ;ROCESS CONTRO7 AND INSTRUMENTATION
Objectives
To create an awareness of the different transducers used in industry and signalconditioning
To familiariBe the process control elements and their control characteristics
Mod4%e I ", 'o4!s(Si$nal Conditionin$ A 7nalo$ A Di$ital - Si$nal con.ersions - Process Control Princi2les Identiication o elements/ block dia$ram/ the loo2/ control s)stem e.aluation stabilit)/ re$ulation/e.aluation criteria/ and c)clic res2onse
Mod4%e II ")0 'o4!s(Fin$% Con!o% E%emen5 9inal control o2eration/ si$nal con.ersions/ analo$ electrical si$nal/ di$italelectrical si$nals/ Direct action A 2neumatic si$nals/ 7ctuators A electrical actuators/ 2neumaticactuators/ control elements A luid .al.es Si$nal Conditionin$ o Transducers- Tem2eratureTransducers - lo3 transducers
Mod4%e III ")2'o4!s(Controller Princi2les - Process characteristics/ control s)stem 2arameters/ controller modes/discontinuous controller modes/ continuous controller modes/ com2osite controller modes7nalo$ Controllers - Electronic controller A Direct action/ re.erse action/ 2ro2ortional mode/ inte$ralmode/ deri.ati.e mode/ com2osite controller modes Pneumatic controllers A im2lementation o PI/PID/ PD Desi$n consideration
Mod4%e I/ ")1'o4!s(Con!o% 7oo3 C'$!$&e!isi&s5 Control s)stem coni$urations/ cascade control/ multi.ariable control/eed or3ard control/ S2lit ran$e control/ inerential control/ 7da2ti.e control/