Matlab code for unit impulse signal generation: clc; clear all all; ; close all all; ; disp('Unit disp('Unit Impulse Signal Generation'); Generation'); N=input('Enter N=input('Enter no of samples: '); '); n=-N:1:N; x=[zeros(1,N),1,zeros(1,N)]; stem(n,x); xlabel('Sample' xlabel('Sample'); ); ylabel('Amplitude' ylabel('Amplitude'); ); title('Unit title('Unit Impulse Signal'); Signal');
In this, the impulse is generated by using ZEROS(x,y) function, which produces an array of size X,Y with all elements as ZERO.
Matlab code for unit ramp signal generation: clc; clear all; close all; disp('Unit Ramp Signal Generation'); N=input('Enter no of samples: '); a=input(' Max Amplitude: '); n=-N:1:N; x=a*n/N; stem(n,x); xlabel('Sample'); ylabel('Amplitude'); title('Unit Ramp Signal');
Matlab code for unit step (delayed step) signal generation: clc;
clear all; close all;
disp('Delayed Unit Step Signal Generation'); N=input('Enter no of samples: '); d=input('Enter delay value: '); n=-N:1:N; x=[zeros(1,N+d),ones(1,N-d+1)]; stem(n,x); xlabel('Sample'); ylabel('Amplitude'); title('Delayed Unit Step Signal');
Matlab code for discrete sinusoidal signal generation: clc; clear all; close all; disp('Sinusoidal Signal generation'); N=input('Enter no of samples: '); n=0:0.1:N; x=sin(n); figure, stem(n,x); xlabel('Samples'); ylabel('Amplitude'); title('Sinusoidal Signal');
The SIN(n) function returns an array which corresponds to sine value of the array ‘n’
Matlab code for discrete cosine signal generation: clc; clear all; close all; disp('Cosine wave generation'); N=input('Enter no of samples'); n=0:0.1:N; x=cos(n); figure, stem(n,x); xlabel('Samples'); ylabel('Amplitude'); title('Cosine');
The COS(n) function returns an array which corresponds to cosine value of the array ‘n’
clc;clear all; n=input('Enter the no samples: '); x=0:0.1/n:20; s=sawtooth(x); t=sawtooth(x,0.5); % width=0.5 for Triangular signal subplot(2,1,1), plot(x,s), xlabel('Time'), ylabel('Amplitude'), title('Sawtooth signal'); subplot(2,1,2), plot(x,t),title('Triangular signal'), xlabel('Time'), ylabel('Amplitude');
Matlab code for exponentially decaying signal generation:
clc; clear all; close all; disp('Exponential decaying signal'); N=input('Enter no of samples: '); a=1; t=0:0.1:N; x=a*exp(-t); figure,plot(t,x); xlabel('Time'); ylabel('Amplitude');
title('Exponentially Decaying Signal');
Matlab code for exponentially growing signal generation: clc; clear all; close all; disp('Exponential growing signal'); N=input('Enter no of samples: '); a=1; t=0:0.1:N; x=a*exp(t); figure,stem(t,x); xlabel('Time'); ylabel('Amplitude'); title('Exponentially Decaying Signal');
http://www.elecdude.com/2013/01/matlab-code-for-circular-convolution.html
MATLAB PROGRAM TO DISPLAY THE PROPERTIES OF DISCRETE FOURIER TRANSFORM (DFT) - LINEARITY PROPERTY
%DFT linearity property close all; clear all; N=input('Howmany point DFT do you want?'); x1=input('Enter the first sequence=');
x2=input('Enter the second sequence='); a=input('Enter the first constant a='); b=input('Enter the second constant b='); n1=length(x1); n2=length(x2); c=zeros(N); x1=[x1 zeros(1,N-n1)];%make both x1 and x2 x2=[x2 zeros(1,N-n2)];%of same dimension x3=a*x1 x4=b*x2 x5=x3+x4 %a*x1+b*x2 for k=1:N for n=1:N w=exp((-2*pi*i*(k-1)*(n-1))/N); %prev.step=>evaluating w-matrix x(n)=w; end c(k,:)=x; %Every row of w-matrix is inserted & end
%finally c becomes the w matrix %for n-point DFT
r1=c*x1'; %x1(k) r2=c*x2'; %x2(k) R3=a*r1+b*r2 %a*x1(k)+b*x2(k) R4=c*x5'
%DFT of a*x1(n)+b*x2(n)
%plotting magnitude and angle subplot(211) stem(abs(R4)); title('DFT of {a*x1(n)+b*x2(n)}'); subplot(212) stem(angle(R3)); title('DFT of {a*x1(k)+b*x2(k)}');
MATLAB PROGRAM TO DISPLAY THE PROPERTIES OF DISCRETE FOURIER TRANSFORM (DFT) - MULTIPLICATION PROPERTY
%multiplication property x1(n)*x2(n)=(1/N)*circonv(X1(k)*X2(k)) clear all; x1=input('enter the sequence='); x2=input('enter the second seq of same length='); N9=input ('enter the number of samples='); x3=(x1).*(x2); %multiplication of 2 signals x4=fft(x1,N9);%dft of first seq N1=length(x4);%length of sequence
x5=fft(x2,N9);%dft of secnd sequence N2=length(x5);%length of second sequence %finding circonvolution of 2 signals x=x4; h=x5; N1=length(x); N2=length(h); N=max(N1,N2); x=[x zeros(1,N-N1)]; h=[h zeros(1,N-N2)]; for n=0:N-1 y(n+1)=0; for i=0:N-1 j=mod(n-i,N); y(n+1)=y(n+1)+x(i+1)*h(j+1); end end y=y/N; %rhs x6=fft(x3,N); %lhs n=0:1:N-1;
subplot(121); stem(n,x6); title('dft of 2 multiplied signals'); grid on; subplot(122); stem(n,y); title('Nth part of circular convolution of 2 dfts'); grid on;
MATLAB PROGRAM TO IMPLEMENT THE PROPERTIES OF DISCRETE FOURIER TRANSFORM (DFT) - FREQUENCY SHIFT PROPERTY
%dft frequecy shift property close all; clear all; N=input('how many point dft do you want?'); x1=input('enter the seq'); n2=length(x1); c=zeros(N); x1=[x1 zeros(1,N-n2)];
for k=1:N for n=1:N w=exp((-2*pi*i*(k-1)*(n-1))/N); x(n)=w; end c(k,:)=x; end disp('dft is '); r=c*x1'; a1=input('enter the amount of shift in frequency domain'); for n=1:N w=exp((2*pi*i*(n-1)*(a1))/N); x2(n)=w; end r1=x2.*x1; subplot(221); stem(abs(r)); grid on; title('orginal dft magnitude plot'); subplot(222);
stem(angle(r)); grid on; title('orginal dft angle'); for k=1:N for n=1:N w=exp((-2*pi*i*(k-1)*(n-1))/N); x(n)=w; end c(k,:)=x; end disp('dft is'); r2=c*r1'; subplot(223); stem(abs(r2)); grid on; title('shifted dft magnitude'); subplot(224); stem(angle(r2)); grid on; title('shifed dft angle');
MATLAB PROGRAM TO IMPLEMENT THE PROPERTIES OF DISCRETE FOURIER TRANSFORM (DFT) - CONVOLUTION PROPERTY
clear all; x= input ('enter the first sequence'); h= input ('enter the second sequence'); No=input('number of samples?'); N1= length(x); N2= length(h);
N=max(N1,N2);%length of sequence x=[x zeros(1,N-N1)]; %modified first sequence h=[h zeros(1,N-N2)]; %modified second sequence
for n=0:N-1; y(n+1)=0; for i=0:N-1 j=mod(n-i,N); y(n+1)=y(n+1)+x(i+1)*h(j+1); %shifting and adding end end n=0:1:No-1; x4=fft(x); x5=fft(h); x6=fft(y); %seq 2 subplot(121) stem(n,x6); title('dft of two convoluted signals'); x7=(x4).*(x5);%product of two dfts
subplot(122); stem(n,x7); title('product of two dfts'); grid on;
EFFECT OF RECTANGULAR | HAMMING | HANNING | BLACK MAN WINDOWS ON FIR lowpass filter clear all; close all; f=input('enter the freq'); N=input('enter the number of samples'); w=2*pi*f; alpha=(N-1)/2; h=zeros(1,N); for n=0:1:N-1 if n~=(N-1)/2 h(n+1)=sin(w*(n-alpha))/((n-alpha)*pi); h(n+1)=1-h(n+1); end end h(((N-1)/2)+1)=w/pi; rectangular_window=boxcar(N); ham=hamming(N); han=hanning(N);
black=blackman(N); h1=h.*rectangular_window'; h2=h.*ham'; h3=h.*han'; h4=h.*black'; w=0:.01:pi; H1=freqz(h1,1,w); H2=freqz(h2,1,w); H3=freqz(h3,1,w); H4=freqz(h4,1,w); plot(w/pi,abs(H1),'r',w/pi,abs(H2),'g',w/pi,abs(H3),'y',w/pi,abs(H4)); OUTPUT enter the freq 0.3*pi
enter the samples 33
