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LABORATORY MANUAL

ECE 303 and ECE353

Unified Electronics Lab-III

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S.No Name of the Experiments Sr no

MATLAB

1. To develop program for designing an FIR and IIR filter 3

2. To develop a program for Computing discrete Convolution and Correlation 10

3. To develop a program for Computing Circular Convolution 13

4. To develop a program for Computing DFT and IDFT in MATLAB

5. To develop a program for Computing Inverse Z-Transform

BREAD BOARD

6. To design and implement on a breadboard a circuit to perform Amplitude

Modulation.

MTE

7. To design and implement on a breadboard a circuit to perform Frequency

Modulation.

8. Compile, Elaborate, and Simulate a 2-to-1 mux Design using IncisiveSimulator

MICROPROCESSOR

9. Interfacing and control of stepper motor using 8085 microprocessor.

10. Generation of delay in binary counting using 8085 microprocessor.

11. To implement a moving 7-segment display with suitable delay using 8085

microprocessor.

12. Write a program to interface two digit numbers using seven Segment

LEDs, use 8086 microprocessor and 8255 PPI.

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FIR filters

AIM: To verify FIR filters.

EQUIPMENTS:

ConstructorMATLAB Software

THEORY:

A Finite Impulse Response (FIR) filter is a discrete linear time-invariant system whoseoutput is based on the weighted summation of a finite number of past inputs. An FIR transversal

filter structure can be obtained directly from the equation for discrete-time convolution.

In this equation, x(k) and y(n) represent the input to and output from the filter at time n.h(n-k) is the transversal filter coefficients at time n. These coefficients are generated by using

FDS (Filter Design Software or Digital filter design package).FIR filter is a finite impulse response filter. Order of the filter should be specified.

Infinite response is truncated to get finite impulse response. placing a window of finite lengthdoes this. Types of windows available are Rectangular, Barlett, Hamming, Hanning, Blackmann

window etc. This FIR filter is an all zero filter.

PROGRAM:

%fir filt design window techniquesclc;

clear all;

close all;

rp=input('enter passband ripple');rs=input('enter the stopband ripple');

fp=input('enter passband freq');fs=input('enter stopband freq');

f=input('enter sampling freq ');wp=2*fp/f;

ws=2*fs/f;num=-20*log10(sqrt(rp*rs))-13;

dem=14.6*(fs-fp)/f;

n=ceil(num/dem);n1=n+1;if(rem(n,2)~=0)

n1=n;n=n-1;

endc=input('enter your choice of window function 1. rectangular 2. triangular 3.kaiser: \n ');

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if(c==1)y=rectwin(n1);

disp('Rectangular window filter response');end

if(c==2)

y=triang(n1);disp('Triangular window filter response');end

if(c==3)y=kaiser(n1);

disp('kaiser window filter response');end

%LPFb=fir1(n,wp,y);

[h,o]=freqz(b,1,256);m=20*log10(abs(h));

subplot(2,2,1);plot(o/pi,m);title('LPF');

ylabel('Gain in dB-->');xlabel('(a) Normalized frequency-->');

%HPFb=fir1(n,wp,'high',y);

[h,o]=freqz(b,1,256);m=20*log10(abs(h));

subplot(2,2,2);plot(o/pi,m);title('HPF');

ylabel('Gain in dB-->');xlabel('(b) Normalized frequency-->');

%BPFwn=[wp ws];

b=fir1(n,wn,y);[h,o]=freqz(b,1,256);

m=20*log10(abs(h));subplot(2,2,3);plot(o/pi,m);

title('BPF');ylabel('Gain in dB-->');

xlabel('(c) Normalized frequency-->');%BSF

b=fir1(n,wn,'stop',y);[h,o]=freqz(b,1,256);

m=20*log10(abs(h));subplot(2,2,4);plot(o/pi,m);

title('BSF');ylabel('Gain in dB-->');

xlabel('(d) Normalized frequency-->')

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RESULTS:

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if(c==2)disp('Frequency response of IIR HPF is:');

[b,a]=butter(n,wn, 'high','s');end

w=0:.01:pi;

[h,om]=freqs(b,a,w);m=20*log10(abs(h));an=angle(h);

figure,subplot(2,1,1);plot(om/pi,m);title('magnitude response of IIR filter is:');

xlabel('(a) Normalized freq. -->');ylabel('Gain in dB-->');

subplot(2,1,2);plot(om/pi,an);title('phase response of IIR filter is:');

xlabel('(b) Normalized freq. -->');ylabel('Phase in radians-->');

RESULTS:

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LINEAR CONVOLUTION AND CORRELATION

AIM: To verify Linear Convolution.

EQUIPMENTS:Software -- MATLAB 7.5

THEORY:Convolution is a formal mathematical operation, just as multiplication, addition, and

integration. Addition takes twonumbers and produces a thirdnumber, while convolution takestwosignals and produces a thirdsignal. Convolution is used in the mathematics of many fields,

such as probability and statistics. In linear systems, convolution is used to describe therelationship between three signals of interest: the input signal, the impulse response, and the

output signal.

In this equation, x1(k), x2(n-k) and y(n) represent the input to and output from the system

at time n. Here we could see that one of the input is shifted in time by a value every time it ismultiplied with the other input signal. Linear Convolution is quite often used as a method of

implementing filters of various types.

ALGORITHM:

1. Enter the input Sequence ,x having length=42. Enter the Impulse Sequence, h having length=4

3. Performing the Convolution, store the value in y4. Plotting the Input Sequence.5. Plotting the Impulse Sequence.6. Plotting the Output Sequence.

PROGRAM:

%linear convolution programclc;

clear all;close all;

disp('linear convolution program');x=input('enter i/p x(n):');

m=length(x);h=input('enter i/p h(n):');

n=length(h);x=[x,zeros(1,n)];

subplot(2,2,1), stem(x);

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title('i/p sequencce x(n)is:');xlabel('---->n');

ylabel('---->x(n)');grid;h=[h,zeros(1,m)];

subplot(2,2,2), stem(h);

title('i/p sequencce h(n)is:');xlabel('---->n');ylabel('---->h(n)');grid;

disp('convolution of x(n) & h(n) is y(n):');y=zeros(1,m+n-1);

for i=1:m+n-1y(i)=0;

for j=1:m+n-1if(j

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%program for discrete Correlation

x=[1 2 3 4];

y=[2 3 4 5];z=xcorr(x,y);stem(z);

subplot(2,2,1),stem(x)title(input sequence 1)

subplot(2,2,2),stem(y)title(input sequence 2)

subplot(2,2,3),stem(z)title(output sequence)

ALGORITHM:

1 Enter the input Sequence ,x having length=4

2 Enter the Impulse Sequence, y having length=43 Performing the Correlation, store the value in y

4 Plotting the Output Sequence ,store in z.

RESULT:

1 2 3 40

1

2

3

4input sequence 1

1 2 3 40

2

4

6input sequence 2

0 2 4 6 80

10

20

30

40output sequence

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CIRCULAR CONVOLUTION

AIM: To verify Circular Convolution.

EQUIPMENTS:Software - MATLAB 7.5

THEORY:

Circular convolution is another way of finding the convolution sum of two input signals.It resembles the linear convolution, except that the sample values of one of the input signals is

folded and right shifted before the convolution sum is found. Also note that circular convolutioncould also be found by taking the DFT of the two input signals and finding the product of the

two frequency domain signals. The Inverse DFT of the product would give the output of thesignal in the time domain which is the circular convolution output. The two input signals could

have been of varying sample lengths. But we take the DFT of higher point, which ever signalslevels to. For eg. If one of the signal is of length 256 and the other spans 51 samples, then we

could only take 256 point DFT. So the output of IDFT would be containing 256 samples insteadof 306 samples, which follows N1+N2 1 where N1 & N2 are the lengths 256 and 51

respectively of the two inputs. Thus the output which should have been 306 samples long isfitted into 256 samples. The 256 points end up being a distorted version of the correct signal.

This process is called circular convolution.

PROGRAM:

%circular convolution programclc;clear all;close all;disp('circular convolution program');x=input('enter i/p x(n):');m=length(x);h=input('enter i/p sequence h(n)');n=length(h);subplot(2,2,1), stem(x);title('i/p sequencce x(n)is:');xlabel('---->n');ylabel('---->x(n)');grid;subplot(2,2,2), stem(h);title('i/p sequencce h(n)is:');

xlabel('---->n');ylabel('---->h(n)');grid;disp('circular convolution of x(n) & h(n) is y(n):');if(m-n~=0)

if(m>n)h=[h,zeros(1,m-n)];n=m;

end

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x=[x,zeros(1,n-m)];m=n;

endy=zeros(1,n);y(1)=0;a(1)=h(1);for j=2:n

a(j)=h(n-j+2);end

%ciruclar convfor i=1:n

y(1)=y(1)+x(i)*a(i);end

for k=2:ny(k)=0;

% circular shiftfor j=2:n

x2(j)=a(j-1);endx2(1)=a(n);

for i=1:nif(i

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DFT AND IDFTAIM: To develop a program for Computing DFT and IDFT in MATLAB

REQUIREMENTS: MATLAB 7.5

THEORY:The discrete Fourier transform (DFT) X[k] of a finite-length sequence x[n] can be easily

computed in MATLAB using the function fft. There are two versions of this function. fft(x)computes the DFTX[k] of the sequencex[n] where the length ofX[k] is the same as that ofx[n].

fft(x,L) computes the L-point DFT of a sequence x[n] of lengthNwhereL N. IfL > N, x[n] iszero-padded with LN trailing zero-valued samples before the DFT is computed. The inverse

discrete Fourier transform (IDFT) x[n] of a DFT sequenceX[k] can likewise be computed usingthe function ifft, which also has two versions.

PROGRAM CODE:

% Program to perform Discrete Fourier Transform

clc;clear all; close all hidden;x=input('The given sequence is x(n): ');

N=length(x);

for k=1:N

X(k)=0;

for n=1:N

X(k)=X(k)+x(n).*exp(-j.*2.*pi.*(n-1).*(k-1)./N);

end

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end

display('The DFT of the given sequence is:')

X

p=0:(N-1);

stem(p,abs(X)),grid

Input Sequence:-

ALGORITHM:

1 Enter the input Sequence ,x having length=4

2 Set the range of k according to the length of x.3 Computing DFT, store the value in X(k).4 Plotting the DFT of given Sequence,store in X(k).

RESULT:

0 0.5 1 1.5 2 2.5 30

2

4

6

8

10

12

14

16

18

20

Fig shows DFT of input sequence

% Program to perform Inverse Discrete Fourier Transform

clc;clear all; close all hidden;

x=input('The given sequence is x(n): ');

N=length(x);

for k=1:N

X(k)=0;

for n=1:N

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X(k)=X(k)+x(n).*exp(j.*2.*pi.*(n-1).*(k-1)./N);

end

end

display('The DFT of the given sequence is:')

X

p=0:(N-1);

stem(p,abs(X)),grid

Input Sequence:

ALGORITHM:

1 Enter the input Sequence, x having length=42 Set the range of k according to the length of x.

3 Computing IDFT, store the value in X(k).4 Plotting the IDFT of given Sequence, store in X(k).

RESULT:

0 0.5 1 1.5 2 2.5 30

1

2

3

4

5

6

7

8

9

10

Fig shows IDFT of input sequence

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INVERSE Z TRANSFORM

AIM: To develop a program for Computing Inverse Z-Transform

EQUIPMENTS: MATLAB 7.5

THEORY:Description: In mathematics and signal processing, the Z-transform converts a discrete

time-domain signal, which is a sequence of real or complex numbers, into a complex frequency-

domain representation. The Z-transform, like many other integral transforms, can be defined aseither a one-sided or two-sided transform.

The bilateral or two-sided Z-transform of a discrete-time signal x[n] is the function X(z)

defined as

.

Alternatively, in cases where x[n] is defined only for n 0, the single-sided or unilateral

Z-transform is defined as

In signal processing, this definition is used when the signal is causal.

Rational Z-transform to partial fraction form:Consider the transfer function in the rational form i-e;

http://en.wikipedia.org/wiki/Signal_processinghttp://en.wikipedia.org/wiki/Causal_systemhttp://en.wikipedia.org/wiki/Causal_systemhttp://en.wikipedia.org/wiki/Signal_processing

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18z3

G(z)= ------------------

18z3+3z

2-4z-1

We can evaluate the partial fraction form of the above system using matlab command. The

partial fraction form be,

G(z)= 0.36__ + __0.24__ + _0.4____10.5z-1

1+0.33 z-1

(1+0.33 z-1

)

Matlab command that converts rational z-transform in to partial fraction form is

residuez.If you want to see the poles and zeros in a zplane. This function displays the poles and zeros

of discrete-time systems. Use the under given matlab command

zplane(b,a)

PROGRAM CODE:

%program to perform Inverse Z-Transform

b=[1,0.4*sqrt(2)];

a=[1,-0.8*sqrt(2),0.64];[R,P,C]=residuez(b,a);

m=abs(P');

subplot(1,2,1);

plot(m);

title('magnitude');

A=angle(P')/pi;

subplot(1,2,2);

plot(A);

title('Angle');

freqz(a,b,10)

ALGORITHM:

1. Write the poles and zeros of the input sequence.2. Returned vector R contains the residues,Column vector contains P contains the pole

locations. And row vector contains the direct terms.3. Plot the pole magnitudes.4. Plot the pole angles in pi units.5. Plot the frequency response of given z-transform of the given function.

Input Sequence:

RESULT: MAGNITUDE AND ANGLE:-

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0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

0

50

100

150

Normalized Frequency ( rad/sample)

Phase(degrees)

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-20

-10

0

10

20

Normalized Frequency ( rad/sample)

Ma

gnitude(dB)

1 1.5 2-0.5

0

0.5

1

1.5

2magnitude

1 1.5 2-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25Angle

Experiment no 6AIM : To design and implement on a breadboard a circuit to perform Amplitude modulation.

APPARATUS: Two IC BC 107BP,33k, 100k,two 4.7k,270ohm resistor, two 4.7F capacitor,CRO(20 Mhz),Function generator(1Mhz),connecting wires and probes.

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PROCEDURE:-1. Connect the circuit as per the given circuit diagram.

2. Apply fixed frequency carrier signal to carrier input terminals.3. Apply modulating signal from function generator of 1VP-P of 500Hz.

4. Note down and trace the modulated signal envelop on the CRO screen. 5. Find the modulationindex by measuring Vmax and Vmin from the modulated (detected/ traced) envelope.

M=(VmaxVmin)/(Vmax+Vmin)6. Repeat the steps 3,4 & 5 by changing the frequency or/& amplitude of the modulating signal

so as to observe over modulation, under modulating and perfect modulation.7. For demodulation, apply the modulated signal (A.M) as an input to the demodulator and verify

the demodulated output with respect to the applied modulating signals and their respectiveoutputs.

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Observed m= (Vmax + V min) / (V maxV min )

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ERROR ANALYSIS: Calculate Modulation index using mathematical formula mc = Vm/Vc.

%AGE ERROR = ((mmc)/ mc)x100% RESULT:

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Experiment no 7

AIM : To design and implement on a breadboard a circuit to perform Frequency modulation.

APPARATUS: IC LM 2206,10k, two 100k,three 4.7k,220ohm resistor,22F,1F,10F,0.01F,CRO(20 Mhz),Function generator(1Mhz),connecting wires and probes. CIRCUIT DIAGRAM:

1. Connect the circuit as per the given circuit diagram.2. 2. Apply the modulating signal of 500HZ with 1Vp-p.3. Trace the modulated wave on the C.R.O & plot the same on graph.4. Find the modulation index by measuring minimum and maximum frequency deviations

from the carrier frequency using the CRO. M = S/f = maximum Frequency deviation /

modulating signal frequency5. Repeat the steps 3& 4 by changing the amplitude and /or frequency of the modulatingSignal.

EXPECTED WAVEFORMS

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OBSERVATION TABLEFormula used: m f= / fm

where = k Vm fcK is the proportionality constant

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Result

Experiment no.-8AIM: Compile, Elaborate, and Simulate a 2-to-1 mux Design using Incisive Simulator.

Equipment: CADENCEIncisive SimulatorTheory: Incisive Simulator is created for verification teams developing complex system-level

environments, Cadence Incisive Enterprise Simulator simplifies and accelerates yourworkflow. Its blend of leading-edge process automation technology, high-performance engines,

power analysis, and advanced debug capabilitiesintegrated with the Incisive platformhelpsyou verify the most complex chips and systems. With support for all IEEE-standard languages,

Si2s Common Power Format, and the comprehensive Plan-to-Closure Methodology, IncisiveEnterprise Simulator improves productivity, project predictability, and product quality, helping

you take the risk out of verification.

Flow Chart:

INCISIVE ENTERPRISE SIMULATOR: Incisive Enterprise Simulator is the only product onthe market that supports all IEEE-standard languages and design abstractions, from the gate levelall the way up to system modeling and verification. Additionally it supports the verification plan

(v-Plan) executable specification, Si2s Common Power Format (CPF) specification, and allPlan-to-Closure Methodology flows. Verification engineers can extend the functionality of

Enterprise Simulator with Incisive Software Extensions that provide a high-throughput channelbetween the test-bench and the device under test (DUT), and enables automated Plan-to-Closure

verification of embedded software exactly as if it were another part of the DUT. With otherelements from the Incisive platform, including verification IP, hardware acceleration and

emulation, analog/mixed-signal/RF verification, and formal assertion verification, EnterpriseSimulator supports any test-bench, HDL, CPF file, software, and assertion IP created with the

Incisive platforms other simulators: the HDL Simulator and the Design Team Simulator; or v-Plans created by Enterprise Manager.

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Experiment -8AIM Interfacing 8x8 keyboard using 8085 microprocessor.

Apparatus required Push Switches (64)SAMPLE PROGRAM:

Block Diagram

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Source program

MVI A, 90H : Initialize Port A as input andOUT CR : Port B as Output

START: MVI A, 00 : Make all scan lines zero

OUT PB

BACK: IN PA

CPI FF : Check for key release

JNZ BACK : If not, wait for key release

CALL DELAY : Wait for key debounce

BACK 1: IN PA

CPI FF : Check for key press

JZ BACK 1 : If not, wait for key pressCALL DELAY : Wait for key debounce

MVI L, 00H : Initialize key counter

MVI C, 08H

MVI B, FEH : Make one column low

NEXTCOL: MOV A, B

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OUT PB

MVI D, 08H : Initialize row counter

IN PA : Read return line status

NEXTROW: RRC : Check for one row

JNC DISPLAY : If zero, goto display else continue

INR L : Increment key counterDCR D : Decrement row counter

JNZ NEXTROW : Check for next row

MOV A, B

RLC : Select the next column

MOV B, A

DCR C : Decrement column count

JNZ NEXTCOL : Check for last column if not repeat

JMP START : Go to start

INTERFACING SCHEME

Delay subroutine:

Delay: LXI D, Count

Back: DCX D

MOV A, D

ORA E

JNZ Back

RET

FLOWCHART

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Conclusion A stepper motor is a digital motor. It can be driven by digital signal. Fig. shows thetypical 2 phase motor rated 12V /0.67 A/ph interfaced with the 8085 microprocessor system

using 8255. Motor shown in the circuit has two phases, with center-tap winding. The center tapsof these windings are connected to the 12V supply. Due to this, motor can be excited by

grounding four terminals of the two windings. Motor can be rotated in steps by giving proper

excitation sequence to these windings. The lower nibble of port A of the 8255 is used to generateexcitation signals in the proper sequence. These excitation signals are buffered using drivertransistors. The transistors are selected such that they can source rated current for the

windings.Motor is rotated by 1.80 per excitation.____________________________________________________________________________

Experiment 9AIM Generation of delay in binary counting using 8085 microprocessor .SAMPLE PROGRAM Write a program for displaying binary up counter. Counter should count

numbers from 00 to FFH and it should increment after every 0.5 sec.

Source Program:

LXI SP, 27FFH : Initialize stack pointerMVI C, OOH : Initialize counter

BACK: CALL Display : Call display subroutineCALL Delay : Call delay subroutine

INR C : Increment counterMOV A, C CPI OOH : Check counter is > FFH

JNZ BACK : If not, repeatHLT : Stop

Delay Subroutine:

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Delay: LXI B, count : Initialize countBACK: DCX D : Decrement count

MOV A, EORA D : Logically OR D and E

JNZ BACK : If result is not 0 repeat RET : Return to main program

Experiment 10

AIM: TO implement a moving 7-segment display with suitable delay using 8085 microprocessor.

Apparatus required 7-segment display

Sample program Interface an 8-digit 7 segment LED display using 8255 to the 8085microprocessor system and write an 8085 assembly language routine to display message on thedisplay.

INTERFACING SCHEME

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CONCLUSIONFig. shows the multiplexed eight 7-segment display connected in the 8085 system using 8255. In

this circuit port A and port B are used as simple latched output ports. Port A provides the

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Experiment 11Aim:Write a program to interface two digit numbers using seven Segment LEDs, use 8086microprocessor and 8255 PPI

Apparatus required 7-segment display

Flow Chart

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Circuit Diagram

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Conclusion

Fig. shows the interfacing of eight 7-segment digits to 8085 through 8279. As shown in

the figure eight display lines (Bo-B3 and Ao-A3) are buffered with the help of transistor

and used to drive display digits. These buffered lines are connected in parallel to all

display digits. So, Sl and S2 lines are decoded and decoded lines are used for selection

of one of the eight digits

Source program:

LXI B, 6200B : Initialize lookup table pointer

MVI C, 08H : Initialize counter

MVI A, 00H : Initialize keyboard/display

OUT 8IH : Mode

MVI A, 3EH : Initialize prescaler count

OUT 8IH

MVI A, 90H : Initial size 8279 in write Display

OUT 8IH : RAM-mode

BACK : MOV A, M : Get the 7-segment code

OUT 80H : Write 7-segment code in display RAM

INX H : Increment lookup table pointer

DCR C : Decrement counter

JNZ BACK : if count = 0 stop, otherwise go to back

HLT : Stop program execution