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How can I Implement a convolution function in MATLAB and perform it on the following signals and plot the results ?

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Hi guys,
I have the following function:
impulse_response = zeros(1, length(input) + length(delta) - 1 );
for t_samp = 1:length(input)
for c_samp = 1:length(delta)
index = t_samp + c_samp - 1;
value = delta(c_samp) * input(t_samp);
impulse_response(index) = impulse_response(index) + value;
end
end
I am new to Matlab and I want to understand how to Implement a convolution function in MATLAB and perform it on the following signals and plot the results ?
Task (1):
x[n] = [1,1,1,1] h[m] = [1,0,−1] x[n] = sin(n) h[m] = [−1,−2,8,−2,−1] 20 ≤ n < 20
Task (2): Given the input signal x[n]=0.3∗sin(n/5)+sin(n/50) : -Create your own delta signal h[m] that removes the higher frequency sinusoidal component to get yl[n].
Thanks in advance for your kind explanation.
  2 Kommentare
Vaban Dust
Vaban Dust am 15 Mär. 2018
Hi Walter, thanks for your quick reply. Actually our instructor didn't mention anything about n values type but let's presume they are radians not degrees

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Akzeptierte Antwort

Abraham Boayue
Abraham Boayue am 16 Mär. 2018
Hey Vaban, you already got a code that implements convolution in matlab, all you need to do is to use it to solve your exercises: Alternatively, you could use matlab built in function called conv(), but it seems like your teacher wants you to learn how to code in matlab. Here is how you can use the code you have. Ex. Task 1.
% This is just a cleaner code, same as the one you posted
clear variables
close all
n = -20:20;
x = sin(n);
h = [-1,-2,8,-2,-1];
N = length(x);
M = length(h);
Ny = N + M -1;
y = zeros(1,Ny);
for i = 1:N
for k = 1:M
y(i+k-1) = y(i+k-1) + h(k)*x(i);
end
end
m = 0: Ny-1;
% Make plot
figure
stem(m,y,'linewidth',3,'color','m')
grid;
a = title('Output of an LTI System y(n)');
set(a,'fontsize',14);
a = ylabel('y(n)');
set(a,'Fontsize',14);
a = xlabel('n');
set(a,'Fontsize',14);
% Using matlab built in function (you get the same results)
figure
y2 = conv(x,h);
stem(m,y2,'linewidth',3,'color','r')
grid;
a = title('Output y(n) using conv(x,h)');
set(a,'fontsize',14);
a = ylabel('y(n)');
set(a,'Fontsize',14);
a = xlabel('n ');
set(a,'Fontsize',14);
% % input = [1 1 1 1]; % input = x (n) = [1 1 1 1]
% % delta = [1 0 -1]; % h(m) = [-1 0 1]
% impulse_response = zeros(1, length(input) + length(delta) - 1 );
% for t_samp = 1:length(input)
% for c_samp = 1:length(delta)
% index = t_samp + c_samp - 1;
% value = delta(c_samp) * input(t_samp);
% impulse_response(index) = impulse_response(index) + value;
% end
% end
% Ny = length(input) + length(delta)-1;
% y = impulse_response;
% m = 0:Ny-1;
% % plot
% stem(m,y,'linewidth',3,'color','b')
% grid;
% a = title('Output of an LTI System y(n)');
% set(a,'fontsize',14);
% a = ylabel('y(n)');
% set(a,'Fontsize',14);
% a = xlabel('n [1 4]');
% set(a,'Fontsize',14);
  3 Kommentare
Niklas Endler
Niklas Endler am 20 Okt. 2020
Correct me if I'm wrong but this only works in cases where the step function h[m] is symmetric?
Walter Roberson
Walter Roberson am 20 Okt. 2020
discrete convolution and discrete filtering are the same mathematical operation, but they use the opposite convention on whether the matrix is applied left-to-right or right-to-left.
>> conv([1 2 3],[1 2 3])
ans =
1 4 10 12 9
>> conv([1 2 3],fliplr([1 2 3]))
ans =
3 8 14 8 3
conv() essentially flips the second vector and moves the result from left to right across the first vector; assume that there are zeros outside the first vector. This operation is thematically consistent with continuous convolution, as opposed to

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Weitere Antworten (3)

Abhishek Ballaney
Abhishek Ballaney am 15 Mär. 2018
Bearbeitet: Walter Roberson am 20 Okt. 2020

Ankur Agrawal
Ankur Agrawal am 21 Sep. 2021
Bearbeitet: Walter Roberson am 29 Dez. 2021
n = -20:20;
x = sin(n);
h = [-1,-2,8,-2,-1];
N = length(x);
M = length(h);
Ny = N + M -1;
y = zeros(1,Ny);
for i = 1:N
for k = 1:M
y(i+k-1) = y(i+k-1) + h(k)*x(i);
end
end
m = 0: Ny-1;

Abdullah Mohmmed
Abdullah Mohmmed am 29 Dez. 2021
Write a MATLAB code to calculate and plot the two-sided convolution between the two discrete time signals x(n) and h(n) shown below
  1 Kommentar
Walter Roberson
Walter Roberson am 29 Dez. 2021
No signal definitions were shown.
And if they had been, we would have just referred you to the discussion above, which includes full code.

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