Introduction 2 DSP

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Course OutlineIntroduction to Digital Signal Processing

ET317 : Digital Signal Processing

An Introduction

V. R. Gupta

Assistant Professor

Department of Electronics and Telecommuiction Engineering

Y. C. College of Engineering, Nagpur

December 12, 2013

V. R. Gupta Assistant Professor ET317 : Digital Signal Processing
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Outline

1 Course OutlinesyllabusCourse Objectives

Course OutcomesPrerequisitesCourse Assessment

2 Introduction to Digital Signal Processing

What is Signal?What is Signal Processing?Pros and Cons of Digital Signal ProcessingApplications of Digital Signal Processing

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syllabusCourse ObjectivesCourse OutcomesPrerequisitesCourse Assessment

course outline

Course Code : ET317

Course Name : Digital Signal processing

Course Teacher : V. R. Gupta

Class Room : ET-203Office : DSP Lab

Office Hours : 9.00 am to 4.00 pm.

Phone : 09665381684

Email : [email protected]

Number of Lectures per Week : 03

Number of Tutorials per Week : 01

Lab. hours per week : 02

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Syllabus

Unit:1:Discrete time systems and Discrete Fourier transform:

Review of discrete time systems and their analysis

The Discrete Fourier Transform

Computation of DFT

Properties of DFT

Finding convolution of long data sequences

FFT algorithms: Decimation in time, Decimation inFrequency & radix-n algorithms.


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Syllabus

Unit:2: Digital filter structures:

Block diagram representation.

Equivalent structures.

Basic FIR structures.

Basic IIR structures.

All pass filters.

IIR tapped cascaded lattice structures.

FIR cascaded lattice structures.


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Syllabus

Unit:3: Architectures For Programmable DSP Devices :

Basic Architectural features, DSP Computational Building

Blocks, Bus Architecture and Memory, Data AddressingCapabilities, Address Generation Unit, Programmability andProgram Execution, Speed Issues, Features for Externalinterfacing.

Execution Control and Pipelining: Hardware looping,

Interrupts, Stacks, Relative Branch support, Pipelining andPerformance, Pipeline Depth, Interlocking, Branching effects,Interrupt effects, Pipeline Programming models.


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Syllabus

Unit:4: Programmable Digital Signal Processors:

Commercial Digital signal-processing Devices

Data Addressing modes of TMS320C6XXX DSPsMemory space of TMS320C6XXX Processors

Program Control

TMS320C6XXX instructions and Programming

On-Chip PeripheralsInterrupts of TMS320C6XXX processors

Pipeline Operation of TMS320C6XXX Processors.


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Syllabus

Unit:5: IIR Filter Design:

Bilinear transformation

Impulse invariant transformation

Lowpass IIR digital filter

Butterworth filter

Chebyshev filterSpectral transformations


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Syllabus

Unit:6: FIR Filter Design:

Filter design using windowing techniquesFrequency sampling technique

Lowpass IIR digital filter

Park Mc Clellen Method of FIR filter

Design Remez Exchange Algorithm


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Books

Text Books

Digital signal processing- A computer based approach By S.K. Mitra,2nd Edition,Tata McGraw Hill, 2002

Discrete time signal processingBy V. Oppenheim, R. W.

Schafer,2nd Edition,PHI, 2008

Reference Books

Digital signal processing Principles, algorithms and

applicationsBy J. G. Proakis, D. G. Manolakis,2ndEdition,PHI, 2002.

Digital Signal Processors, Architecture, Programming and

ApplicationsBy Venkataramani, Bhaskar,2nd Edition,TataMcGraw Hill, 2008.

Introduction to DSPby JohnyR Johnson, PHI, 2nd editionV. R. Gupta Assistant Professor ET317 : Digital Signal Processing

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yCourse ObjectivesCourse OutcomesPrerequisitesCourse Assessment


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yCourse ObjectivesCourse OutcomesPrerequisitesCourse Assessment

Course Objectives

To Develop the Decimation in time and frequency FFTalgorithms for efficient computation of the DFT.

Learn the Architectures of programmable DSP processors.

Implement real time applications on DSP processor.Implementing digital filters in a variety of structures: directform I and II, parallel, and cascade.

Design digital filters using transformation techniques fromanalog designs;

Design digital filters using windowing techniques;

Evaluate the performance of a digital filter, in terms of itsfrequency response;

Organize and make technical presentations.


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Course ObjectivesCourse OutcomesPrerequisitesCourse Assessment

Course Outcomes

After successfully completing this course, students will be

able to:

Use Fast Fourier Transform techniques for the analysis ofarbitrary signals;

Programme a DSP processor in assembly or C-language.Implement real time applications on DSP processor such asreal time filter.Apply DSP techniques to real-world signal acquisition,spectral analysis and signal filtering.

Design digital IIR filters by designing prototypical analog filtersand then applying analog to digital conversion techniques.Design digital FIR filters meeting given specifications;Evaluate the performance of a digital filter, in terms of itsfrequency response;

Organize and write technical reports;V. R. Gupta Assistant Professor ET317 : Digital Signal Processing

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Prerequisites

To take this course, you should have knowledge and understandingof

1 ET305-Signals and systems;


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Prerequisites




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Prerequisites




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Course Assessment

1 Home Assignments:= 4%


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Course Assessment


2 Surprise Test:= 2%


C O li

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Course Assessment



3 Quiz:= 2%


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Cou se Object esCourse OutcomesPrerequisitesCourse Assessment

Course Assessment



3 Quiz:= 2%

4 Attendance:= 2%


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jCourse OutcomesPrerequisitesCourse Assessment

Course Assessment



3 Quiz:= 2%

4 Attendance:= 2%

5 Mid Sem. Exam-1:= 15%


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Course Assessment



3 Quiz:= 2%

4 Attendance:= 2%




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Course Assessment



3 Quiz:= 2%

4 Attendance:= 2%



7 End Sem. Exam:= 60%

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Course Outline

syllabusCourse ObjectivesC O t


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Introduction to Digital Signal ProcessingCourse OutcomesPrerequisitesCourse Assessment

Examination

Examination

There will be 2 scheduled exams and at least one Surprise Test asdetailed below. The schedule of these examinations is given in the

Academic Calendar for the session published by the Dean(Academic Matters)

1) Mid Sem. Exam-1: On the basis of Unit 1 & 2.



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Examination

Examination





3) End Sem. Exam : On the basis of Unit 1 to 6


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Examination

Examination





3) End Sem. Exam : On the basis of Unit 1 to 64) Surprise Test : On the topics taught till the day of

examinations.


Course OutlineS

What is Signal?What is Signal Processing?

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Introduction to Digital Signal Processing Pros and Cons of Digital Signal ProcessingApplications of Digital Signal Processing

Introduction to Digital Signal Processing

What is Signal?

Any physical quantity that varies with time, space or any otherindependent variable is called as signal.

Example

speech signal, video signal


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What is Signal?What is Signal Processing?P d C f Di i l Si l P i
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Introduction ..............

Types of Signal

Analog Signal : Continuous in time; Continuous inamplitude.

Discrete Signal : Discrete in time; Continuous in amplitude.

Digital Signal : Discrete in time; Discrete in amplitude.


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What is Signal?What is Signal Processing?P d C f Di it l Si l P i
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Introduction..................

What is Signal Processing?

Signal processing is the analysis, interpretation, and manipulation

of signals like sound, images time-varying measurement values andsensor data etc.

Example

Removing noise from the music signal;

Amplification of a speech signal;



What is Signal?What is Signal Processing?Pros and Cons of Digital Signal Processing
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Introduction..................

Need of Signal Processing

When a signal is transmitted from one point to another there isevery possibility of contamination /deformation of the signal byexternal noise. So to retrieve the original signal at the receiversuitable filters are to be used. i.e the signal is processed to obtainthe pure signal.

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Advantages of Digital Signal Processing

Less sensitive to component tolerances & environmentalchanges.

Volume production without the need for adjustment duringconstruction or use.

Amenable to full integration

Accuracy increases with the increase in word size (but cost )

Dynamic rangeTime multiplexing



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Advantages of Digital Signal Processing

Storage of digital signal

FlexibilityMultirate processing

Easy adjustment of processor characteristics by changing thecoefficients. E.g. adaptive filter, variable cutoff filter

No loading problem due to cascading



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g g g g g gApplications of Digital Signal Processing

Disadvantages of Digital Signal Processing

Sampling causes loss of information

Limited speed of processorsQuantization and round-off errors

Increased complexity

Power dissipation

Sampling rate is limited due to sample & hold , DAC, ADC



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Applications of Digital Signal Processing

Choice of Signal Processing

Finally we make a conclusion that the choice of analog or digitalapproach for the solution of signal processing problem can only bedetermined by the following points.

The application of interest.

The resources available.

The cost involved in building the system.



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The Digital Processing of Signal plays a vital role in almost everyfield of Science and Engineering. Some of the applications ofdigital signal processing in various fields of Science andEngineering are as given below:

Speech ProcessingSpeech compression and decompression to reduce memoryrequirement of storage system.

Speech recognition for voice operated systems and voicebased based security systems.

Speech synthesis for various voice based warnings orannouncements.

Speech compression and decompression for effective use oftransmission channels.



What is Signal?What is Signal Processing?Pros and Cons of Digital Signal ProcessingA li i f Di i l Si l P i
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Communications

The spectrum analysis of modulated signals helps to identify

the information bearing frequency component that can beused for transmission.

The analysis of signals received from radars are used to detectflying objects and their velocity.

Generation and detection of DTMF signals in telephones.Echo and noise cancellation in transmission channels.



What is Signal?What is Signal Processing?Pros and Cons of Digital Signal ProcessingA li ti f Di it l Si l P i
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Biomedical

ECG is used to predict heart diseases.

X-ray images are used to predict the bone fractures andtuberculosis.

Ultrasonic scan images of kidney and gall bladder is used topredict stones.

MRI scan is used to study minute inner details of any part ofhuman body.



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Audio and Video Equipments

The analysis of audio signals will be useful to design systems

for special effects in audio systems like stereo, woofer, karoke,equalizer, attenuator, etc.

Music synthesis and composing using music keyboards.

Audio and Video compression for storage in DVDs.

Filtering operations on images to extract the features orhidden information.



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Image processings

Image compression and decompression to reduce memory

requirement of storage systems.Image compression and decompression for effective use oftransmission channels.

Image recognition for security systems.




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Geology

The seismic signals are used to determine the magnitude of

earthquakes and volcanic eruptions.The seismic signals are also used to predict nuclear explosions.

The seismic noise is also used to predict the movements oeearth layers tectonicplates




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Astronomy

The analysis of light received from a star is used to determinethe condition of the star.

The analysis of images of various celestial bodies gives vitalinformation about them.



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Common DSP Algorithms and Typical Applications

DSP Algorithms System Applications

Digital Cellular Telephone;Speech coding and Decoding Multimedia computers;

secure Communications.

Robotics;Speech recognition Automotive applicationsMultimedia Workstations

Noise Cancellation Professional Audio;Industrial Applications

Beam forming Navigation;RADAR/SONAR

Echo Cancellation Speaker phones;modems



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Typical Applications of DSP

DSP is used in numerous applications :1 video compression

2 digital set-top box

3 cable modems

4 portable video systems/computers5 Digital audio

6 Multimedia and wireless communication

7 Speech processing

8 Digital cameras9 Radar imaging

10 Medical imaging

11 Biomedical signal processing



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Thank You!

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Introduction 2 DSP

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