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DIGITAL SIGNAL PROCESSING LAB Dept. of ECE

1SRI SAI ADITYA INSTITUTE OF SCIENCE & TECHNOLOGY

TABLE OF CONTENTS

S.NO. NAME OF THE EXPERIMENT PAGE NO

1 To study the architecture of DSP chipsTMS 320CSA/Instructions

5

2 To verify Linear Convolution 19

3 To verify Circular Convolution 23

4 To design FIR filter (LP/HP) using Windowing technique:

a. Using Rectangular Windowb. Using Triangular Windowc. Using Kaiser Window 27

5 To design IIR filter (LP/HP) 39

6 5. Npoint FFT algorithm47

7 MATLAB program to generate sum of sinusoidal signal algorithm55

8 MATLAB program to find frequency response of analog LP/HP

filters 59

9 To compute Power Density Spectrum of a sequence 67

10 To find the FFT of given 1-D signal and plot 75

ADDITIONAL EXPERIMENTS

11 Basic signals generation using MATLAB 83

12 Signal smoothing using MATLAB 91

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LAB INTERNAL EVALUATION

S.No Name of the Experiment Date Remarks

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TMS320C6713 DSK Overview Block Diagram

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Expt.No: Date:

TO STUDY THE ARCHITECTURE OF DSP CHIPS

TMS 320 CSA / INSTRUCTIONS

AIM: To study the architecture of DSP processor TMS 320C6713 / Instructions.

TOOLS REQUIRED:

TMS 320 C6713Kit,

Code Composer Studio Software,

Personal Computer

The C6713 Digital Signal Processor (DSP) Starter Kit (DSK) builds on Texas

Instruments (TI's) industry-leading line of low cost, easy-to-use DSK development boards.

The high-performance board features the TMS320C6713 floating-point DSP. Capable of

performing 1350 Million Floating-point Operations Per Second (MFLOPS), the C6713 DSP

makes the C6713 DSK the most powerful DSK development board. The DSK is USB port

interfaced platform that allows to efficiently develop and test applications for the C6713. The

DSK consists of a C6713-based printed circuit board that will serve as a hardware reference

design for TIs customers products. With extensive host PC and target DSP software

support, including bundled TI tools, the DSK provides ease-of-use and capabilities that are

attractive to DSP engineers.

The C6713 DSK has a TMS320C6713 DSP onboard that allows full-speed verification of

code with Code Composer Studio. The C6713 DSK provides:

A USB Interface SDRAM and ROM An analog interface circuit for Data conversion (AIC) An I/O port Embedded JTAG emulation support

The C6711 DSK includes a stereo codec. This analog interface circuit (AIC) has the

following characteristics:

1. High-Performance Stereo Codec 90-dB SNR Multibit Sigma-Delta ADC (A-weighted at 48 kHz) 100-dB SNR Multibit Sigma-Delta DAC (A-weighted at 48 kHz) 1.42 V3.6 V Core Digital Supply: Compatible With TI C54x DSP Core

Voltages 2.7 V3.6 V Buffer and Analog Supply: Compatible Both TI C54x DSP

Buffer Voltages

8-kHz96-kHz Sampling-Frequency Support

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2. Software Control Via TI McBSP-Compatible Multiprotocol Serial Port I 2 C-Compatible and SPI-Compatible Serial-Port Protocols Glueless Interface to TI McBSPs

3. Audio-Data Input/Output Via TI McBSP-Compatible Programmable Audio Interface I 2 S-Compatible Interface Requiring Only One McBSP for both ADC and

DAC

Standard I 2 S, MSB, or LSB Justified-Data Transfers 16/20/24/32-Bit Word Lengths

The C6713DSK has the following features:

The 6713 DSK is a low-cost standalone development platform that enables customers to

evaluate and develop applications for the TI C67XX DSP family. The DSK also serves as a

hardware reference design for the TMS320C6713 DSP. Schematics, logic equations and

application notes are available to ease hardware development and reduce time to market.

The DSK uses the 32-bit EMIF for the SDRAM (CE0) and daughter card expansion interface(CE2 and CE3). The Flash is attached to CE1 of the EMIF in 8-bit mode.

An on-board AIC23 codec allows the DSP to transmit and receive analog signals. McBSP0

is used for the codec control interface and McBSP1 is used for data. Analog audio I/O is

done through four 3.5mm audio jacks that correspond to microphone input, line input, line

output and headphone output. The codec can select the microphone or the line input as the

active input. The analog output is driven to both the line out (fixed gain) and headphone

(adjustable gain) connectors. McBSP1 can be re-routed to the expansion connectors in

software.

The DSK includes 4 LEDs and 4 DIP switches as a simple way to provide the user with

interactive feedback. Both are accessed by reading and writing to the CPLD registers.

An included 5V external power supply is used to power the board. On-board voltage

regulators provide the 1.26V DSP core voltage, 3.3V digital and 3.3V analog voltages. A

voltage supervisor monitors the internally generated voltage, and will hold the board in reset

until the supplies are within operating specifications and the reset button is released. If

desired, JP1 and JP2 can be used as power test points for the core and I/O power supplies.

Code Composer communicates with the DSK through an embedded JTAG emulator with a

USB host interface. The DSK can also be used with an external emulator through the

external JTAG connector.

TMS320C6713 DSP Features

Highest-Performance Floating-Point Digital Signal Processor (DSP): Eight 32-Bit Instructions/Cycle 32/64-Bit Data Word 300-, 225-, 200-MHz (GDP), and 225-, 200-, 167-MHz Clock Rates 3.3-, 4.4-, 5-, 6-Instruction Cycle Times 2400/1800, 1800/1350, 1600/1200, and 1336/1000 MIPS /MFLOPS Rich Peripheral Set, Optimized for Audio Highly Optimized C/C++ Compiler Extended Temperature Devices Available

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TMS320C6713 DSP Block Diagram

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Advanced Very Long Instruction Word (VLIW) TMS320C67x DSP Core Eight Independent Functional Units:

Two ALUs (Fixed-Point) Four ALUs (Floating- and Fixed-Point) Two Multipliers (Floating- and Fixed-Point)

Load-Store Architecture with 32 32-Bit General-Purpose Registers Instruction Packing Reduces Code Size All Instructions Conditional

Instruction Set Features Native Instructions for IEEE 754

Single- and Double-Precision Byte-Addressable (8-, 16-, 32-Bit Data) 8-Bit Overflow Protection Saturation; Bit-Field Extract, Set, Clear; Bit-Counting; Normalization

L1/L2 Memory Architecture 4K-Byte L1P Program Cache (Direct-Mapped) 4K-Byte L1D Data Cache (2-Way) 256K-Byte L2 Memory Total: 64K-Byte L2 Unified Cache/Mapped RAM, and 192K-

Byte Additional L2 Mapped RAM

Device Configuration Boot Mode: HPI, 8-, 16-, 32-Bit ROM Boot Endianness: Little Endian, Big Endian

32-Bit External Memory Interface (EMIF) Glueless Interface to SRAM, EPROM, Flash, SBSRAM, and SDRAM 512M-Byte Total Addressable External Memory Space

Enhanced Direct-Memory-Access (EDMA) Controller (16 Independent Channels) 16-Bit Host-Port Interface (HPI) Two Multichannel Audio Serial Ports (McASPs)

Two Independent Clock Zones Each (1 TX and 1 RX) Eight Serial Data Pins Per Port:

Individually Assignable to any of the Clock Zones

Each Clock Zone Includes: Programmable Clock Generator Programmable Frame Sync Generator TDM Streams From 2-32 Time Slots Support for Slot Size:

8, 12, 16, 20, 24, 28, 32 Bits

Data Formatter for Bit Manipulation Wide Variety of I2S and Similar Bit Stream Formats Integrated Digital Audio Interface Transmitter (DIT) Supports:

S/PDIF, IEC60958-1, AES-3, CP-430 Formats Up to 16 transmit pins Enhanced Channel Status/User Data

Extensive Error Checking and Recovery Two Inter-Integrated Circuit Bus (I2C Bus) Multi-Master and Slave Interfaces

Two Multichannel Buffered Serial Ports: Serial-Peripheral-Interface (SPI) High-Speed TDM Interface AC97 Interface

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Procedure used for running Code Composer Studio:

1. Click on the Code Composer Studio. And create the project of your own i.e. as shownbelow:

2. To create the new source file, Click on File-> NEW-> Source file

3. Write the program in edit window and save the file in your project as *.C (for C

Program) or *.asm (Assembly Language Program)

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TMS320C6713 CPU Datapath

Two 32-Bit General-Purpose Timers Dedicated GPIO Module With 16 pins (External Interrupt Capable) Flexible Phase-Locked-Loop (PLL) Based Clock Generator Module IEEE-1149.1 (JTAG ) Boundary-Scan-Compatible Package Options:

208-Pin Power PAD Plastic (Low-Profile) Quad Flat pack (PYP) 272-BGA Packages (GDP and ZDP)

0.13-m/6-Level Copper Metal Process CMOS Technology

3.3-V I/Os, 1.2 -V Internal (GDP & PYP) 3.3-V I/Os, 1.4-V Internal (GDP)(300 MHz only)The TMS320C6713 CPU contains :

1. Program Fetch unit2. Instruction dispatch unit3. Instruction decode unit4. Two data paths, each with four functional units5. 32 32-bit registers6. Control registers7. Control logic8. Test, emulation, and interrupt logic

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4. Click on Project ->Add files to Project-> click your Source file.

5. Click on Project ->Add files to Project ->C:\CCStudio\cgtools\lib\rts6700.lib

(File type is Object and Library Files *.o, *.l)

6. Click Project ->Add files to Project -:\CCStudio\Tutorial\dsk6713\hello1\hello.cmd(File type is Linker Command File *.cmd)

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Mapping Between Instructions and Functional Units : The following Table shows which

instructions can be executed in which of the functional units for fixed point instructions.

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6. Click on Project -> Compile your file.

8. Click on Project-> Build your File.

9. Click on File-> Load project.

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Mapping Between Instructions and Functional Units : The following Table shows which

instructions can be executed in which of the functional units for floating point instructions.

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10. Disassembly file is available in the below Window.

11. Click on Debug -> Run (see the result in the Output window.)

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Program:

.global _main

_main:

MVKL .S1 -5, A4

ABS .L1 A4, A4

ZERO .L1 A3ADD .L1 A4, A4, A3

SUB .L1 A3, A4, A5

MPY .M1 A3, A4, A0

NOP 1

SUB .L2X A0, B0, B0

B B3

NOP 5

RESULT:

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MODEL GRAPH:

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Expt.No: Date:

TO VERIFY LINEAR CONVOLUTION

AIM: To write a program to compute the response of a discrete LTI system with input

sequence x(n) and impulse response h(n) by using linear convolution.

TOOLS REQUIRED:

TMS 320 C6713Kit,


Personal Computer

PROCEDURE:

1. Create a Project in Code Composer Studio.2. Create a Source file in C language for Linear Convolution and add it to the project.3. Add both hello.cmd & rts6700.lib files to the current project folder from the

following locations:

C:\CCStudio\tutorial\dsk6713\hello1 and C:\CCStudio\c6000\cgtools\lib

4. Compile C file for debugging errors.5. Build the project.6. Load Program (.out file) into DSK from file menu.7. Run the program from Debug menu.8. Plot the Graph of linear convolution from Viewgraph menu.

C-PROGRAM FOR LINEAR CONVOLUTION:

#include

int x[20],h[20],y[20],N1,N2,n,m;

main()

{

printf("Enter the length of input sequence x(n)\t:N1=");

scanf("%d",&N1);

printf("Enter the length of impulse response h(n)\t:N2=");

scanf("%d",&N2);

printf("Enter %d samples for input sequence x(n):\n",N1);

for(n=0;n

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GRAPH:

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for(n=0;n

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MODEL GRAPH:

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Expt.No: Date:

TO VERIFY CIRCULAR CONVOLUTION

AIM: To write a program to compute the response of a discrete LTI system with input

sequence x(n) and impulse response h(n) by using Circular convolution.

TOOLS REQUIRED:

TMS 320 C6713Kit,


Personal Computer

PROCEDURE:

1. Create a Project in Code Composer Studio.2. Create a Source file in C language for Circular Convolution and add it to the project.3. Add both hello.cmd & rts6700.lib files to the current project folder from the



4. Compile C file for debugging errors.5. Build the project.6. Load Program (.out file) into DSK from file menu.7. Run the program from Debug menu.8. Plot the Graph of Circular convolution from Viewgraph menu.

C-PROGRAM FOR CIRCULAR CONVOLUTION:

#include

int m,n,x[30],h[30],y[30],i,j,temp[30],k,x2[30],a[30];

void main()

{

printf(" enter the length of the first sequence\n");

scanf("%d",&m);

printf(" enter the length of the second sequence\n");

scanf("%d",&n);

printf(" enter the first sequence\n");

for(i=0;i

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GRAPH:

CALUCLATION:

Enter the length of input sequence x(n) :N1=

Enter the length of impulse response h(n):N2=

Enter 4 samples for input sequence x(n):

Enter 4 samples for impulse response h(n):

Input sequence after zero padding

x(n)=

Impulse Response after zero padding

h(n)=

Response of LT1 system is

y(n)=

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{ if(m>n) /* Pad the smaller sequence with zero*/

for(i=n;i

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OUTPUT: Rectangular Window

OUTPUT: Triangular Window

0 0.5 1-60

-40

-20

0

Gain in dB -->

Normalised

0 0.5 1-40

-20

0

20

Gain in dB -->

Normalised

0 0.5 1-60

-40

-20

0Gain in dB -->

Normalised

0 0.5 1-15

-10

-5

0

5Gain in dB -->

Normalised

0 0.5 1-100

-50

0

50Gain in dB -->

Normalised

0 0.5 1-100

-50

0

50Gain in dB -->

Normalised

0 0.5 1-100

-50

0

50Gain in dB -->

Normalised

0 0.5 1-60

-40

-20

0

20Gain in dB -->

Normalised

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Expt.No: Date:

DESIGN OF FIR FILTER USING WINDOWING

TECHNIQUES

AIM: To write a program to design a FIR filters using different windowing techniques.

TOOLS REQUIRED:

MATLAB Software,

Personal Computer.

ALGORITHM:

1. Get the pass band and stop band ripples.

2. Get the pass band and stop band edge frequencies.

3. Get the sampling frequency.

4. Calculate the order of filter.

5. Find filter coefficients.

6. Draw the magnitude and phase response.

MATLAB PROGRAM FOR FIR FILTER USING RECTANGULAR WINDOW:

clc;

clear all;

close all;

fp=input('enter the pass band frequency');

fs=input('enter the stop band frequency');

rp=input('enter the pass band ripple');

rs=input('enter the stop band ripple');

f=input ('enter the sample frequency');

wp=2*fp;

ws=2*fs;w1=wp/f;

w2=ws/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;

end

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Kaiser window:

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%low pass filter

y=boxcar(n1);

n1

b=fir1(n,w1,y);

[h,o]=freqz(b,1,256);

m=20*log10(abs(h));

subplot(2,2,1);

plot(o/pi,m);

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

xlabel('Normalised frequency');

%high pass filter

y=boxcar(n1);

n1

b=fir1(n,w1,'high',y);

[h,o]=freqz(b,1,256);

m=20*log10(abs(h));

subplot(2,2,2);

plot(o/pi,m);



%band pass filter

wn=[w2 w1];

y=boxcar(n1);

wn

n1

b=fir1(n,wn,y);

[h,o]=freqz(b,1,256);

m=20*log10(abs(h));

subplot(2,2,3);

plot(o/pi,m);



%band stop filter

wn=[w2 w1];

y=boxcar(n1);

n1

b=fir1(n,wn,'stop',y);

[h,o]=freqz(b,1,256);

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Gaph:

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m=20*log10 (abs(h));

subplot(2,2,4);

plot(o/pi,m);



MATLAB PROGRAM FOR FIR FILTER USING TRIANGULAR WINDOW:

clc;

clear all;

close all;






wp=2*fp;

ws=2*fs;

w1=wp/f;

w2=ws/f;


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

n=ceil(num/dem);

n1=n+1;

if(rem(n,2)~=0)

n1=n;

n=n-1;

end

%low pass filter

y=triang(n1);

n1

b=fir1(n,w1,y);

[h,o]=freqz(b,1,256);

m=20*log10(abs(h));

subplot(2,2,1);

plot(o/pi,m);



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Graph:

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%high pass filter

y=triang(n1);

n1


[h,o]=freqz(b,1,256);

m=20*log10(abs(h));

subplot(2,2,2);

plot(o/pi,m);



%band pass filter

wn=[w2 w1];

y=triang(n1);

n1

b=fir1(n,wn,y);

[h,o]=freqz(b,1,256);

m=20*log10(abs(h));

subplot(2,2,3);

plot(o/pi,m);



%band stop filter

wn=[w2 w1];

y=triang(n1);

n1


[h,o]=freqz(b,1,256);

m=20*log10(abs(h));

subplot(2,2,4);

plot(o/pi,m);



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Graph:

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MATLAB PROGRAM FOR FIR FILTER USING KAISER WINDOW:

clc;

clear all;

close all;

beta=0.5;






wp=2*fp;

ws=2*fs;

w1=wp/f;

w2=ws/f;


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

n=ceil(num/dem);

n1=n+1;

if(rem(n,2)~=0)

n1=n;n=n-1;

end

%low pass

y=kaiser(n1,beta);

b=fir1(n,w1,y);

[h,o]=freqz(b,1,256);

m=20*log10(abs(h));

subplot(2,2,1);

plot(o/pi,m);



%high pass

y=kaiser(n1,beta);


[h,o]=freqz(b,1,256);

m=20*log10(abs(h));

subplot(2,2,2);

plot(o/pi,m);

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%band pass

y=kaiser(n1,beta);

wn=[w2 w1];

wn

n1

b=fir1(n,wn,y);

[h,o]=freqz(b,1,256);

m=20*log10(abs(h));

subplot(2,2,3);

plot(o/pi,m);



%band stop

y=kaiser(n1,beta);

wn=[w2 w1];


[h,o]=freqz(b,1,256);

m=20*log10(abs(h));

subplot(2,2,4);

plot(o/pi,m);



RESULT:

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OUTPUT:

OUTPUT:

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-400

-300

-200

-100

0

(a) Normalised frequency

Gain in dB

BUTTERWORTH HIGH PASS FILTER

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-4

-2

0

(b) Normalised frequency

Phase in radians

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Expt.No: Date:

To design IIR filter (LP/HP)

AIM: Design of IIR Butter worth, Chebyshevhigh pass & low pass digitalfilters using

MATLAB.

TOOLS REQUIRED:

MATLAB Software,

Personal Computer.

MATLAB PROGRAM FOR IIR BUTTERWORTH HIGH PASS FILTER:

clc;

clear all;

close all;






wp=2*pi*fp;

ws=2*pi*fs;

w1=wp/f;

w2=ws/f;

[N,WN]=buttord(w1,w2,rp,rs);

[B,A]=butter(N,WN,'HIGH');

w=0:0.01:pi;

[H1,om]=freqz(B,A,w);

m=20*log10(abs(H1));

an=angle(H1);

subplot(2,1,1);

plot(om/pi,m);

xlabel(' (a) Normalised frequency');

ylabel(' Gain in dB');

title('BUTTERWORTH HIGH PASS FILTER');

grid;

subplot(2,1,2);

plot(om/pi,an);

xlabel(' (b) Normalised frequency');

ylabel(' Phase in radians');

grid;

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MATLAB PROGRAM FOR IIR BUTTERWORTH LOW PASS FILTER

clc;

clear all;

close all;






wp=2*pi*fp;

ws=2*pi*fs;

w1=wp/f;

w2=ws/f;

[N,WN]=buttord(w1,w2,rp,rs);

[B,A]=butter(N,WN,'LOW');

w=0:0.01:pi;

[H1,om]=freqz(B,A,w);


an=angle(H1);

subplot(2,1,1);

plot(om/pi,m);



title('BUTTERWORTH LOW PASS FILTER');

grid;

subplot(2,1,2);

plot(om/pi,an);



grid;

MATLAB PROGRAM FOR IIR CHEBYSHEV HIGH PASS FILTER:

clc;

clear all;

close all;




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Graph:

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wp=2*pi*fp;

ws=2*pi*fs;

w1=wp/f;

w2=ws/f;

[N,WN]=cheb1ord(w1,w2,rp,rs);

[B,A]=cheby1(N,rp,WN,'high');

w=0:0.01:pi;

[H,om]=freqZ(B,A,w);

m=20*log10(abs(H));

an=angle(H);

subplot(2,1,1);

plot(om/pi,m);



title('CHEBYSHEV TYPE-1 HIGH PASS FILTER');

grid;

subplot(2,1,2);

plot(om/pi,an);



grid;

MATLAB PROGRAM FOR IIR CHEBYSHEV LOW PASS FILTER:

clc;

clear all;

close all;fp=input('enter the pass band frequency');





wp=2*pi*fp;

ws=2*pi*fs;

w1=wp/f;

w2=ws/f;

[N,WN]=cheb1ord(w1,w2,rp,rs);

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[B,A]=cheby1(N,rp,WN,'LOW');

Graph:

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w=0:0.01:pi;

[H,om]=freqZ(B,A,w);

m=20*log10(abs(H));

an=angle(H);

subplot(2,1,1);

plot(om/pi,m);



title('CHEBYSHEV LOW PASS FILTER');

grid;

subplot(2,1,2);

plot(om/pi,an);



grid;

RESULT:

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GRAPH PROPERTY DIALOG SETTINGS:

MODEL GRAPH:

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Expt.No: Date:

N-POINT FFT ALGORITHM

AIM: To obtain the frequency spectrum of the given sampled data (input signal) by using

Fast Fourier Transform on TMS320C6713 DSK Kit (or Simulator).

TOOLS REQUIRED:

TMS 320 C6713Kit,


Personal Computer

PROCEDURE:

1. Create a Project in Code Composer Studio.2. Create Source files in C language for Main.C and FFT.C and add them to the project.3. Add both hello.cmd & rts6700.lib files to the current project folder from the



4. Compile C file for debugging errors.5. Build the project.6. Load Program (.out file) into DSK from file menu.7. Run the program from Debug menu.8. Plot the Graph for input and output from Viewgraph menu.

CSOURCE CODE FOR MAIN.C

#include

#define PTS 8 //# of points for FFT

#define PI 3.14159265358979

typedef struct {float real,imag;} COMPLEX;

void FFT(COMPLEX *Y, int n); //FFT prototype

float iobuffer[PTS]; //as input and output buffer

float x1[PTS],a[PTS]={1,1,1,1,2,2,2,2},y1[PTS],y2[PTS];

short i; //general purpose index variable

short buffercount = 0; //number of new samples in iobuffer

short flag = 0; //set to 1 by ISR when iobuffer full

COMPLEX w[PTS]; //twiddle constants stored in w

COMPLEX samples[PTS]; //primary working buffer

main()

{

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for (i = 0 ; i

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int leg_diff; //difference between upper/lower leg

int num_stages = 0; //number of FFT stages (iterations)

int index, step; //index/step through twiddle constant

i = 1; //log(base2) of N points= # of stages

do

{

num_stages +=1;

i = i*2;

}while (i!=N);

leg_diff = N/2; //difference between upper&lower legs

step = (PTS*2)/N; //step between values in twiddle.h // 512

for (i = 0;i < num_stages; i++) //for N-point FFT

{

index = 0;

for (j = 0; j < leg_diff; j++)

{ for (upper_leg = j; upper_leg < N; upper_leg += (2*leg_diff))

{

lower_leg = upper_leg+leg_diff;

temp1.real = (Y[upper_leg]).real + (Y[lower_leg]).real;

temp1.imag = (Y[upper_leg]).imag + (Y[lower_leg]).imag;

temp2.real = (Y[upper_leg]).real - (Y[lower_leg]).real;

temp2.imag = (Y[upper_leg]).imag - (Y[lower_leg]).imag;

(Y[lower_leg]).real = temp2.real*(w[index]).real - temp2.imag*(w[index]).imag;

(Y[lower_leg]).imag = temp2.real*(w[index]).imag + temp2.imag*(w[index]).real;

(Y[upper_leg]).real = temp1.real;

(Y[upper_leg]).imag = temp1.imag;

} index += step;

}

leg_diff = leg_diff/2;

step *= 2;

}

j = 0;

for (i = 1; i < (N-1); i++) //bit reversal for resequencing data

{

k = N/2;

while (k

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k = k/2;

} j = j + k;

if (i

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MODEL GRAPH:

0 2 4 6 8 10 12 14 16 18 20-1

0

1

TIME INDEX

AMPLITUDE

SUM OF SIN WAVES

0 2 4 6 8 10 12 14 16 18 20-1

0

1

TIME INDEX

AMPLITUDE

0 2 4 6 8 10 12 14 16 18 20-2

0

2

TIME INDEX

AMPLITUDE

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Expt.No: Date:

MATLAB PROGRAM TO GENERATE SUM OF SINUSOIDAL

SIGNALS

AIM: To generate sum of sinusoidal signals using MATLAB

TOOLS REQUIRED:

MATLAB Software,

Personal Computer.

MATLAB PROGRAM:

clc;

clear all;close all;

t=0:0.01:20;

x1=sin(2*pi*t/5);

subplot(3,1,1);

plot(t,x1);

xlabel('TIME INDEX');

ylabel('AMPLITUDE');

title('SUM OF SIN WAVES');

x2=sin(2*pi*t/7);

subplot(3,1,2);

plot(t,x2);



x=x1+x2;

subplot(3,1,3);plot(t,x);



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Graph:

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Result:

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OUTPUT:

OUTPUT:

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 .8 0.9 1-400

-300

-200

-100

0


Gain in dB

CHEBYSHEV TYPE-1 HIGH PASS FILTER

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 .8 0.9 1-4

-2

0

2

4


Phase in radians

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-1000

-500

0

500


Gain in dB

BUTTERWORTH HIGH PASS FILTER

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-4

-2

0

2

4


Phase in radians

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Expt.No: Date:

MATLAB PROGRAM TO FIND FREQUENCY RESPONSE OF

ANALOG LP/HP FILTERS

AIM: Design of IIR Butter worthand ChebyshevLP/HP filters using MATLAB.

TOOLS REQUIRED:

MATLAB Software,

Personal Computer.

MATLAB PROGRAM FOR ANALOG BUTTERWORTH HIGH PASS FILTER:

clc;

clear all;

close all;






wp=2*pi*fp; ws=2*pi*fs;

w1=wp/f; w2=ws/f;

[N,WN]=buttord(w1,w2,rp,rs,'s');

[B,A]=butter(N,WN,'HIGH','s');

w=0:0.01:pi;

[H1,om]=freqs(B,A,w);


an=angle(H1);

subplot(2,1,1);

plot(om/pi,m);



title('BUTTERWORTH HIGH PASS FILTER');

grid;

subplot(2,1,2);

plot(om/pi,an);



grid;

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OUTPUT:

OUTPUT:

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-150

-100

-50

0


Gain in dB

CHEBYSHEV LOW PASS FILTER

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 14

2

0

2

4


Phase in radians

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-300

-200

-100

0

100


Gain in dB

BUTTERWORTH LOW PASS FILTER

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-4

-2

0

2

4


Phase in radians

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MATLAB PROGRAM FOR ANALOG CHEBYSHEV HIGH PASS FILTER:

clc;

clear all;

close all;






wp=2*pi*fp;

ws=2*pi*fs;

w1=wp/f;

w2=ws/f;

[N,WN]=cheb1ord(w1,w2,rp,rs,'s');

[B,A]=cheby1(N,rp,WN,'high','s');

w=0:0.01:pi;

[H,om]=freqs(B,A,w);

m=20*log10(abs(H));

an=angle(H);

subplot(2,1,1);

plot(om/pi,m);



title('CHEBYSHEV TYPE-1 HIGH PASS FILTER');

grid;

subplot(2,1,2);

plot(om/pi,an);



grid;

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Graph:

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MATLAB PROGRAM FOR ANALOG BUTTERWORTH LOW PASS FILTER:

clc;

clear all;

close all;

fp=input('enter the pass band frequency');fs=input('enter the stop band frequency');




wp=2*pi*fp;

ws=2*pi*fs;

w1=wp/f;

w2=ws/f;

[N,WN]=buttord(w1,w2,rp,rs,'s');

[B,A]=butter(N,WN,'LOW','s');

w=0:0.01:pi;

[H1,om]=freqs(B,A,w);


an=angle(H1);

subplot(2,1,1);plot(om/pi,m);



title('BUTTERWORTH LOW PASS FILTER');

grid;

subplot(2,1,2);

plot(om/pi,an);



grid;

MATLAB PROGRAM FOR ANALOG CHEBYSHEV LOW PASS FILTER:

clear all;

close all;


fs=input('enter the stop band frequency');rp=input('enter the pass band ripple');

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Graph:

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wp=2*pi*fp;

ws=2*pi*fs;

w1=wp/f;

w2=ws/f;

[N,WN]=cheb1ord(w1,w2,rp,rs,'s');

[B,A]=cheby1(N,rp,WN,'LOW','s');

w=0:0.01:pi;

[H,om]=freqs(B,A,w);

m=20*log10(abs(H));

an=angle(H);

subplot(2,1,1);

plot(om/pi,m);



title('CHEBYSHEV LOW PASS FILTER');

grid;

subplot(2,1,2);

plot(om/pi,an);



grid;

RESULT:

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Graph:

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Expt.No: Date:

TO COMPUTE POWER DENSITY SPECTRUM OF A

SEQUENCE

AIM: To write a Program to compute non real time Power Spectral Density.

TOOLS REQUIRED:

TMS 320 C6713Kit,


Personal Computer

PROCEDURE:





C-SOURCE CODE FOR PSD.C

#include


#define PI 3.14159265358979


void FFT(COMPLEX *Y, int n); //FFT prototypefloat iobuffer[PTS]; //as input and output buffer

float x1[PTS],x[PTS]; //intermediate buffer




float y[128];



main()

{

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MODEL GRAPH:

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float j,sum=0.0 ;

int n,k,i,a;

for (i = 0 ; i

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MODEL GRAPH:

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do

{

num_stages +=1;

i = i*2;

}while (i!=N);




{

index = 0;


{

for (upper_leg = j; upper_leg < N; upper_leg += (2*leg_diff))

{






(Y[lower_leg]).real = temp2.real*(w[index]).real -temp2.imag*(w[index]).imag;

(Y[lower_leg]).imag = temp2.real*(w[index]).imag +temp2.imag*(w[index]).real;



}

index += step;

} leg_diff = leg_diff/2;

step *= 2;

} j = 0;


{

k = N/2;

while (k

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j = j - k;

k = k/2;

} j = j + k;

if (i

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OUTPUT:

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Expt.No: Date:

TO FIND THE FFT OF GIVEN 1-D SIGNAL AND PLOT

AIM: To find the FFT of a given 1-D signal and plot the graph.

TOOLS REQUIRED:

TMS 320 C6713Kit,


Personal Computer

PROCEDURE:





CSOURCE CODE FOR MAIN.C

#include


#define PI 3.14159265358979


void FFT(COMPLEX *Y, int n); //FFT prototype

float iobuffer[PTS]; //as input and output buffer

float x1[PTS]; //intermediate buffer






main(){

for (i = 0 ; i

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w[i].imag =-sin(2*PI*i/(PTS*2.0)); //Im component of twiddle constants

}

for (i = 0 ; i < PTS ; i++) //swap buffers

{ iobuffer[i] =sin(2*pi*5*i/(PTS)); /*10- > freq,100 -> sampling freq*/

samples[i].real=0.0;

samples[i].imag=0.0;

}

for (i = 0 ; i < PTS ; i++) //swap buffers

{

samples[i].real=iobuffer[i]; //buffer with new data

iobuffer[i] = x1[i]; //processed frame to iobuffer

}

for (i = 0 ; i < PTS ; i++)

samples[i].imag = 0.0; //imag components = 0

FFT(samples,PTS); //call function FFT.c

for (i = 0 ; i < PTS ; i++) //compute magnitude

{

x1[i] = sqrt(samples[i].real*samples[i].real

+ samples[i].imag*samples[i].imag); ///32;

}

}

CSOURCE CODE FOR FFT.C



extern COMPLEX w[PTS]; //twiddle constants stored in w

void FFT(COMPLEX *Y, int N) //input sample array, # of points

{

COMPLEX temp1,temp2; //temporary storage variables

int i,j,k; //loop counter variables

int upper_leg, lower_leg; //index of upper/lower butterfly leg





do

{

num_stages +=1;

i = i*2;

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}while (i!=N);




{

index = 0;


{

for (upper_leg = j; upper_leg < N; upper_leg += (2*leg_diff))

{






(Y[lower_leg]).real = temp2.real*(w[index]).real -temp2.imag*(w[index]).imag;

(Y[lower_leg]).imag = temp2.real*(w[index]).imag +temp2.imag*(w[index]).real;



}

index += step;

}

leg_diff = leg_diff/2;

step *= 2;

}

j = 0;


{

k = N/2;

while (k

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temp1.imag = (Y[j]).imag;

(Y[j]).real = (Y[i]).real;

(Y[j]).imag = (Y[i]).imag;

(Y[i]).real = temp1.real;

(Y[i]).imag = temp1.imag;

}

}

return;

}

RESULT:

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OUTPUT:

OUTPUT:

-5 0 5 10 150

0.5

1

time

amplitud

UNIT STEP SEQUENCE

-5 0 5 10 150

0.5

1

time

amplitud

DELAYED UNIT STEP SEQUENCE

-5 0 5 10 150

0.5

1

time

amplitud

UNIT SAMPLE SEQUENCE

-5 0 5 10 150

0.5

1

time

amplitud

DELAYED UNIT SAMPLE SEQUENCE

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Expt.No: Date:

BASIC SIGNALS GENERATION USING MATLAB

AIM: Generation of basic signals using MATLAB.

TOOLS REQUIRED:MATLAB Software,

Personal Computer.

MATLAB PROGRAM FOR UNIT SAMPLE SEQUENCE:

n = -5:15;

g = [zeros(1,5) 1 zeros(1,15)];

h = [zeros(1,10) 1 zeros(1,10)];

subplot(2,1,1);

stem(n,g);

xlabel('time index');

ylabel('amplitude');

title('UNIT SAMPLE SEQUENCE');

axis([-5 15 0 1.2]);

subplot(2,1,2);

stem(n,h);



title(' DELAYED UNIT SAMPLE SEQUENCE');

axis([-5 15 0 1.2]);

MATLAB PROGRAM FOR UNIT STEP SEQUENCE:

n = -5:15;

i = [zeros(1,5) ones(1,6) zeros(1,10)];

j = [zeros(1,10) ones(1,6) zeros(1,5)];

subplot(2,1,1);

stem(n,i);



title(' UNIT STEP SEQUENCE');

axis([-5 15 0 1.2]);

subplot(2,1,2);

stem(n,j);

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Graph:

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title(' DELAYED UNIT STEP SEQUENCE');

axis([-5 15 0 1.2]);

MATLAB PROGRAM FOR SINE WAVE:

clc;

clear all;

close all;

t=0:.2:10;

y=sin(2*pi*t/5);

subplot(2,1,1);

plot(t,y);xlabel('time index');


title('SINE WAVE');

subplot(2,1,2);

stem(t,y);



title('SINE WAVE');

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OUTPUT:

OUTPUT:

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

0

0.5

1

time

amplitud

UNIT RAMP

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.5

1

time

amplitud

UNIT RAMP

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MATLAB PROGRAM FOR RAMP SIGNAL:

clc;

clear all;

close all;

m=1;

t=0:.1:1;

y=m*t;

subplot(2,1,1);

plot(t,y);



title('UNIT RAMP');

subplot(2,1,2);

stem(t,y);



title('UNIT RAMP');

MATLAB PROGRAM FOR TRIANGULAR WAVE:

clc;

clear all;

close all;

m=-1;

t=0:1:10;

y=m.^t;

subplot(2,1,1);

plot(t,y);


ylabel('amplitude');title('TRIANGULAR WAVE');

subplot(2,1,2);

stem(t,y);



title('TRIANGULAR WAVE');

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OUTPUT:

Graph:

0 1 2 3 4 5 6 7 8 9 10-1

-0.5

0

0.5

1

time index

amplitude

TRIANGULAR WAVE

0 1 2 3 4 5 6 7 8 9 10-1

-0.5

0

0.5

1

time index

amplitude

TRIANGULAR WAVE

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Result:

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OUTPUT:

0 5 10 15 20 25 30 35 40 45 50-5

0

5

10

time index

amplitude

d[n]

s[n]

x[n]

0 5 10 15 20 25 30 35 40 45 500

2

4

6

8

time index

amplitude

y[n]

s[n]

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Expt.No: Date:

MATLAB PROGRAM FOR SIGNAL SMOOTHING

AIM: Write a program for signal smoothing using MATLAB

TOOLS REQUIRED:

MATLAB Software,

Personal Computer.

PROGRAM:

clc;

clear all;

close all;

R = 51;

d = 0.8*(rand(R,1) - 0.5);

m = 0:R-1;

s = 2*m.*(0.9.^m);

x = s+d';

subplot(2,1,1);

plot(m,d','r-',m,s,'g-',m,x,'b-.');



legend('d[n]','s[n]','x[n]');

grid;

x1 = [0 0 x];

x2 = [0 x 0];

x3 = [x 0 0];

y = (x1 + x2 + x3)/3;

subplot(2,1,2);

plot(m,y(2:R+1),'r-',m,s,'g-.');

legend('y[n]','s[n]');



grid;

Result:

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Graph:

Documents

Final Dsp Lab 2-06-12