This repository contains MATLAB scripts for various signal-processing experiments. Each experiment demonstrates different aspects of signal processing techniques, such as plotting, generating, time-scaling, convolution, and more.
Experiment demonstrating plotting Sin and Cos waves overlapping using MATLAB's plot and stem functions.
x = 0:0.1:10;
y = sin (x);
z = cos (x);
subplot (3,1,1);
plot (x,y,'b');
grid on;
xlabel("x");
ylabel("y=sin(x)");
subplot (3,1,2);
plot (x,z,'r');
grid on;
xlabel("x");
ylabel("z=cos(x)");
subplot (3,1,3);
stem (x,z,'r');
grid on;
hold on;
subplot (3,1,3);
stem (x,y,'b');
xlabel("x");
ylabel("y=sin(x), z=cos(x)");
Experiment demonstrating the generation and plotting of a continuous signal.
%2sin(2πτ-π/2)
T = -5:0.05:5;
x = 2*sin((2*pi*T) - (pi/2));
plot (T,x);
grid on;
axis ([-6 6 -3 3])
ylabel ('x(t)')
xlabel ('Time(sec)')
title ('Figure 2.1')
Experiment demonstrating the generation and plotting of a discrete signal.
% Generation of discrete time signals
n = -5:5;
x = [0 0 1 1 -1 0 2 -2 3 0 -1];
stem (n,x);
axis ([-6 6 -3 3]);
xlabel ('n');
ylabel ('x[n]');
title ('Figure 2.2');
Experiment demonstrating the generation and plotting of random sequences.
% Generation of random sequences
n = [0:10];
x = rand (1, length (n));
y = randn (1, length (n));
plot (n,x) ;
grid on;
hold on;
plot(n,y,'r');
ylabel ('x & y')
xlabel ('n')
title ('Figure 2.3');
Experiment demonstrating the generation and plotting of a discrete periodic signal.
n = 0:4;
x = [1 1 2 -1 0];
subplot (2,1,1);
stem (n,x);
grid on;
axis ([-1 15 -1 2]);
xlabel ('n');
ylabel ('x(n)');
title ('Figure 2.4(a)');
xtilde = [x,x,x];
length_xtilde = length (xtilde);
n_new = 0:length_xtilde-1;
subplot (2,1,2);
stem (n_new, xtilde,'r');
grid on;
axis ([-1 length_xtilde -1 2]);
xlabel ('n');
ylabel ('perodic x(n)');
title ('Figure 2.4(b)');
Experiment demonstrating the generation and plotting of a square wave using loops.
clear;
clc;
n = input ('Insert the value of odd n:');
t = 0:.001:1;
sum = 0;
for f = 1:2:n
w = sin (2 * pi * f * t);
sum = sum + w;
end
subplot(1,1,1)
plot(t,sum)
grid on;
xlabel ('Time');
ylabel ('Amplitude');
title ('Square Wave');
Experiment demonstrating the generation and plotting of a unit step discrete time signal.
clc;
clear all;
close all;
N= input('Enter the range: ');
n= -N:1:N;
y= [zeros(1,N),1,ones(1,N)];
stem(n,y);
grid on;
axis([-(N+1) N+1 -0.5 1.5]); % [-x x -y y]
xlabel('Time');
ylabel('Amplitude of Y');
title('Generating Unit Step Function');
Experiment demonstrating different methods to generate and plot a unit impulse signal.
clc;
clear all;
m1 = input('Enter the value of x-axis in negative side:');
m2 = input('Enter the value of x-axis in positive side:');
n = m1:m2;
x = (n==0);%it works as if statement like n=-5:5( 0 0 0 0 0 1 0 0 0 0 0 0)
stem(n,x);
xlabel('n');
ylabel('amplitude');
title('Unit impulse signal');
The unit impulse can be implemented in different way:
clc;
clear all;
close all;
m1 = input('Enter the value of x-axis in negative side:');
m2 = input('Enter the value of x-axis in positive side:');
n = -m1:1:m2;
d = [zeros(1,m1), 1 ,zeros(1,m2)];
stem(n,d);
axis([-m1, m2, -0.5, 1.5])
xlabel('n');
ylabel('Amplitude of Y');
title('Unit impulse signal');
Experiment demonstrating the generation and plotting of a ramp discrete time signal.
close all;
clear all;
clc;
n1 = input ('Enter lower limit'); %-5
n2 = input ('Enter upper limit'); %5
n = n1: 1: n2;
x = n.*[n>=0];
stem (n, x, 'b');
axis([(n1-1) (n2+1) -1 (n2+1)]); % -x,x,-y,y
title ('Ramp Function');
xlabel ('Time');
ylabel ('Amplitude of Y');
grid on;
Experiment demonstrating time reversal of a discrete sinusoidal function using radians for time values.
%close all
%clc
t1 = 0:0.2:2*pi; %values of x-axis in radian
x1 = sin(t1); %values of y-axis
x2 = fliplr(x1); %fliplr() -> this function gives the flipped result;
%lr means left right ...flipud() ud means up down
t2 = -fliplr(t1); % time values must be flipped and negated
subplot(2,1,1)
stem(t1,x1,'LineWidth',2)
xlim([-10 10])
title('Original Signal') %\bf\fontsize{25}
xlabel('Samples (t)')
ylabel('Amplitude (sin(t))')
grid on;
ax = gca;
ax.XAxis.FontSize = 15;
ax.XAxis.FontWeight = 'bold';
ax.YAxis.FontSize = 15;
ax.YAxis.FontWeight = 'bold';
subplot(2,1,2)
stem(t2,x2,'LineWidth',2)
xlim([-10 10])
title('Time Reversed Signal')
xlabel('Samples')
ylabel('Amplitude')
grid on;
ax = gca;
ax.XAxis.FontSize = 15;
ax.XAxis.FontWeight = 'bold';
ax.YAxis.FontSize = 15;
ax.YAxis.FontWeight = 'bold';
Experiment demonstrating time reversal of a discrete sinusoidal function using degrees for time values.
close all
clc
t1=0:10:360; %values of x-axis in degree
x1=sind(t1); % values of y axis
x2=fliplr(x1); %fliplr() -> this function gives the flippefd result;
%lr means left right ...flipud() ud means up down
t2= -fliplr(t1); % time values must be flipped and negated
subplot(2,1,1)
stem(t1,x1,'LineWidth',2)
xlim([-400 400])
ylim([-1.5 1.5])
title('Original Signal')
xlabel('Samples')
ylabel('Amplitude')
grid on;
ax = gca;
ax.XAxis.FontSize = 15;
ax.XAxis.FontWeight = 'bold';
ax.YAxis.FontSize = 15;
ax.YAxis.FontWeight = 'bold';
subplot(212)
stem(t2,x2,'LineWidth',2)
xlim([-400 400])
ylim([-1.5 1.5])
title('Time Reversed Signal') %\bf\fontsize{25}
xlabel('Samples')
ylabel('Amplitude')
grid on;
ax = gca;
ax.XAxis.FontSize = 15;
ax.XAxis.FontWeight = 'bold';
ax.YAxis.FontSize = 15;
ax.YAxis.FontWeight = 'bold';
Experiment demonstrating addition of two signals using MATLAB.
clear all;
clc;
x1=[-5 -4 -3 -2 -1 0];
y1=[2 5 4 6 3 5];
x2=[-2 -1 0 1 2];
y2=[8 9 2 5 6];
% Draw the second signal.
subplot(3,1,1);
stem(x1,y1);
grid on;
grid minor;
axis([-10 10 -8 8]);
% Draw the second signal.
subplot(3,1,2);
stem(x2,y2);
grid on;
grid minor;
axis([-10 10 -2 16]);
n=min(min(x1),min(x2)):1:max(max(x1),max(x2));
% This function is for the addition the two signal .
[y] = add_function(n,x1,x2,y1,y2);
% This is for the plot the added signal.
subplot(3,1,3);
stem(n,y);
grid on;
grid minor;
axis([-10 10 -2 16]);
function[y] = add_function(n,x1,x2,y1,y2)
m1=zeros(1,length(n));
m2=zeros(1,length(n));
temp=1;
for i=1:length(n)
if(n(i)>=min(x1) & n(i)<=max(x1))
m1(i)=y1(temp);
temp=temp+1;
else
m1(i)=0;
end
end
temp=1;
for i=1:length(n)
if(n(i)>=min(x2) & n(i)<=max(x2))
m2(i)=y2(temp);
temp=temp+1;
else
m2(i)=0;
end
end
y=m1+m2;
end
Experiment demonstrating multiplication of two signals using MATLAB.
clc;
clear all;
close all;
x1=[0:0.1:10];
y1=sin(x1);
x2=[-5:0.1:7];
y2=4*sin(x2);
% This plot is for the plotting the graph of (x1,y1).
subplot(3,1,1);
stem(x1,y1);
grid on;
grid minor;
axis([-5 10 -5 5]);
% This plot is for the plotting the graph of (x2,y2);
subplot(3,1,2);
stem(x2,y2);
grid on;
grid minor;
axis([-5 10 -5 5]);
% This line is use for find out the new range of the signal.
n=min(min(x1),min(x2)):0.1:max(max(x1),max(x2));
[m]=mul_function(n,x1,y1,x2,y2);
%This plot is for the plotting the graph of (n,y) multiplicated signal.
subplot(3,1,3);
stem(n,m,'r');
grid on;
grid minor;
axis([-5 10 -5 5]);
function[m]=mul_function(n,x1,y1,x2,y2)
m1=zeros(1,length(n));
m2=m1;
% This loop is use for the fill the loop m1.
temp=1;
for i=1:length(n)
if(n(i)>=min(x1) & n(i)<=max(x1))
m1(i)=y1(temp);
temp=temp+1;
else
m1(i)=0;
end
end
% This loop is use for the fill the loop m2.
temp=1;
for i=1:length(n)
if(n(i)>=min(x2) & n(i)<=max(x2))
m2(i)=y2(temp);
temp=temp+1;
else
m2(i)=0;
end
end
m=m1.*m2;
end
Experiment demonstrating time scaling of a signal.
close all;
clear all;
clc;
start_value = input('Enter the start value: ');%-6
end_value = input('Enter the end value: ');%6
n1 = start_value:end_value;
y=input("Enter the values of signal = "); %[1 0.5 1 0.5 1 0.5 1 0.5 1 0.5 1 0.5 1]
index=1;
n2=(2*start_value):(2*end_value);
value = 2;
for i=1:length(n2)
x1(i)=n2(i);
if(rem(n2(i),value)==0)
y1(i)=y(index);
index=index+1;
else
y1(i)=0;
end
end
subplot(2,1,1);
stem(n1,y,'r');
xlabel("Time");
ylabel("Amplitude");
grid on;
grid minor;
axis([(start_value-1) (end_value+1) -2 2]);
title("Original signal Y[n]=X[n]");
subplot(2,1,2);
stem(x1,y1,'b');
xlabel("Time");
ylabel("Amplitude");
grid on;
grid minor;
axis([(2*start_value-1) (2*end_value+1) -2 2]);
title("Compresion signal Y[n]=X[n/2]");
close all;
clear all;
clc;
n=-6:6;
y=[1 0.5 1 0.5 1 0.5 1 0.5 1 0.5 1 0.5 1];
index=1;
value1=2;
for i=1:length(n)
if(rem(n(i),value1)==0)
x1(index)=n(i)./value1;
y1(index)=y(i);
index=index+1;
end
end
subplot(3,1,1);
stem(n,y);
xlabel("Time domain");
ylabel("Amplitude");
grid on;
axis([-8 8 -0.5 1.5]);
title("Original signal X[n]");
subplot(3,1,2);
stem(x1,y1,'r');
xlabel("Time domain");
ylabel("Amplitude");
grid on;
grid minor;
axis([-8 8 -0.5 1.5]);
title("Compresion signal Y[n] = X[2n]");
index=1;
n2=-12:12;
value2=2;
for i=1:length(n2)
x1(i)=n2(i);
if(rem(n2(i),value2)==0)
y1(i)=y(index);
index=index+1;
else
y1(i)=0;
end
end
subplot(3,1,3);
stem(x1,y1,'b');
xlabel("Time domain");
ylabel("Amplitude");
grid on;
grid minor;
axis([-13 13 -0.5 1.5]);
title("Expanding signal Y[n] = X[n/2]");
Experiment 15: Time Shifted Signals of Sketch the signal x[n], y[n]=x[n-4] and x[n+4], derived from x[n]
Experiment demonstrating time shifting of a signal.
clc;
clear;
n = -5:5;
x = [0 -1 -.5 .5 1 1 1 1 .5 0 0];
subplot(3,1,1);
stem (n,x);
xlabel('Time Sample');
ylabel('Amplitude');
title('Original Signal');
axis([-7 7 min(x)-2 max(x)+2]);
grid on;
grid minor;
m = n+4;
subplot(3,1,2);
stem (m,x);
xlabel('Time Sample');
ylabel('Amplitude');
title('Time right shifted signal');
axis([-7-2+4 7+2+4 min(x)-2 max(x)+2]);
grid on;
grid minor;
l = n-4;
subplot(3,1,3);
stem (l,x);
xlabel('Time Sample');
ylabel('Amplitude');
title('Time left shifted signal');
axis([-7-2-4 7+2-4 min(x)-2 max(x)+2]);
grid on;
grid minor;
Experiment demonstrating decomposition of a signal into even and odd components.
%n = deg2rad(-180:30:180);
n = -2:1:2;
x = [5,5,4,3,1];
%x = cos(n) + sin(n) + (sin(n) .* cos(n));
%x = 1 + n + 3.*(n.*n) + 5.*(n.*n.*n) + 9.*(n.*n.*n.*n);
%x = 1 + n.*(cos(n)) + (n.*n).*(sin(n)) + (n.*n.*n).*(sin(n));
%x = (1 + n.^3) .* (cos(10.*n)).^3;
disp(x);
% Creating mirrored versions for negative indices
x_mirror = fliplr(x); %x_mirror = [1,4,3,5,5]
% even and odd components
xe = (x + x_mirror) / 2; %xe= ( x(n)+x(-n) )/2;
xo = (x - x_mirror) / 2; %xo= ( x(n)-x(-n) )/2;
% Plotting
subplot(4,1,1);
stem(n, x);
grid on;
axis([-3.5 3.5 min(x)-1 max(x)+1]);
xlabel('n');
ylabel('Amplitude');
title('Original Signal');
subplot(4,1,2);
stem(n, x_mirror);
grid on;
axis([-3.5 3.5 min(x_mirror)-0.5 max(x_mirror)+0.5]);
xlabel('n');
ylabel('Amplitude');
title('Reversed Signal');
subplot(4,1,3);
stem(n, xe, 'b');
grid on;
axis([-3.5 3.5 min(xe)-1 max(xe)+1]);
xlabel('n');
ylabel('Amplitude');
title('Even Signal');
subplot(4,1,4);
stem(n, xo, 'b');
grid on;
axis([-3.5 3.5 min(xo)-1 max(xo)+1]);
xlabel('n');
ylabel('Amplitude');
title('Odd Signal');
Experiment demonstrating transformation of a discrete time signal.
clc;
close all;
%orginal signal
n=-6:6;
y=[0 0 0 0 -1 -2 0 2 1 0 0 0 0];
subplot(3,1,1);
stem(n,y);
grid on;
axis([-8 8 -2 2]);
xlabel('n');
ylabel('amplitude ');
title('x[n]');
%shifting the given signal
n1=n-3;
subplot(3,1,2);
stem(n1,y);
grid on;
axis([-8 8 -2 2]);
xlabel('n');
ylabel('amplitude');
title('x[n+3]');
index=1;
for i=1:length(n1)
if(rem(n1(i), 2)== 0)
x1(index)=n1(i) / 2;
y1(index)=y(i);
index=index+1;
end
end
%final signal
subplot(3,1,3);
stem(x1,y1);
grid on;
axis([-8 8 -2 2]);
xlabel('n');
ylabel('amplitude');
title('y[n] = x[2n+3]');
Experiment demonstrating shifting of signals.
%y[n]=x[n-3] and z[n]=x[n+2]
clc;
close all;
%orginal signal
n=-3:3;
y=[-2 0 1 -3 2 -1 3];
subplot(3,1,1);
stem(n,y);
grid on;
axis([-6 7 -4 4]);
xlabel('n');
ylabel('amplitude ');
title('x[n]');
%shifting the given signal
n1=n+3;
subplot(3,1,2);
stem(n1,y);
grid on;
axis([-6 7 -4 4]);
xlabel('n');
ylabel('amplitude');
title('y[n] = x[n-3]');
%shifting the given signal
n2=n-2;
subplot(3,1,3);
stem(n2,y);
grid on;
axis([-6 7 -4 4]);
xlabel('n');
ylabel('amplitude');
title('z[n] = x[n+2]');
Experiment demonstrating convolution of two signals.
clc;
clear all;
close all;
x1=[-1 0 1 2 3 4 5];
y1=[-1 0.5 1 -0.5 0 0 0];
x2=[0 1 2 3 4 5];
h=[0.5 1 -0.5 0.5 0 0];
[n,y]=func_convalution(x1,y1,x2,h);
subplot(3,1,1);
stem(x1,y1);
xlabel('X1');
ylabel('Y1');
title("Given Signal");
subplot(3,1,2);
stem(x2,h);
xlabel('x2');
ylabel('h');
title("Impulse Response");
subplot(3,1,3);
stem(n,y);
xlabel('n');
ylabel('y');
title("Convalution Sum");
function[n , y]=func_convalution(x1,y1,x2,h)
m1=min(x1)+min(x2);
m2=max(x1)+max(x2);
n=m1:m2;
y=conv(y1,h); % build in function s
end
Experiment demonstrating the sinc function.
x = -50:0.1:50;
% Compute sinc(x) while handling division by zero at x = 0
y = sin(x);
z = ones(size(x)); % Initialize z with ones to handle division by zero
idx = find(x ~= 0); % Find indices where x is not equal to 0
z(idx) = y(idx) ./ x(idx); % Compute sinc(x) for non-zero x
% Plotting
subplot(2,1,1);
plot(x, y, 'b');
grid on;
xlabel("x");
ylabel("y = sin(x)");
subplot(2,1,2);
plot(x, z, 'r');
grid on;
xlabel("x");
ylabel("z = sinc(x)");
Experiment demonstrating the aliasing effect.
clc;
clear all;
close all;
frequency =input('Enter the frequency for the signal:\n');
fprintf("Enter the frequency and it must be greater or less than Nyquist frequency\n");
oversampling=input('');
%fprintf("Enter the UnderSampling frequency and it must be Less than %d\n",2*frequency);
%undersampling=input('');
Time_Period = 1/frequency;
tmin=-0.05;
tmax=0.05;
time = linspace(tmin,tmax,400);
amplitude = cos(2*pi*frequency*time);
subplot(4,1,1);
plot(time,amplitude);
grid on; grid minor;
xlabel("Time");
ylabel("Amplitude");
title("orginal Signal");
%Nyquist rate Sampling Part.
nyquist_frequency = 2*frequency;
time1=tmin:(1/nyquist_frequency):tmax;
amplitude1 = cos(2*pi*frequency*time1);
subplot(4,1,2);
plot(time,amplitude);
hold on;
grid on; grid minor;
plot(time1,amplitude1);
title("NyQuist Sampling");
hold off;
if oversampling>nyquist_frequency
%OverSampling Part.
time1=tmin:(1/oversampling):tmax;
amplitude1 = cos(2*pi*frequency*time1);
subplot(4,1,3);
plot(time,amplitude);
hold on;
plot(time1,amplitude1);
grid on; grid minor;
xlabel("Time");
ylabel("Amplitude");
title("OverSampling");
hold off;
else
%OverSampling Part.
time1=tmin:(1/oversampling):tmax;
amplitude1 = cos(2*pi*frequency*time1);
subplot(4,1,3);
plot(time,amplitude);
hold on;
plot(time1,amplitude1);
grid on; grid minor;
xlabel("Time");
ylabel("Amplitude");
title("UnderSampling");
hold off;
end
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