Code : clc clear all close all x=input('Enter the sequence'); n1=input('Enter the time sample range:'); h=fliplr(x); n2=-fliplr(n1); z=[]; for i=1:length(x) g=h.*x(i); z=[z;g]; end [r c]=size(z); k=r+c; t=2; y=[]; cd=0; while(t
Then in that case , it is cross-correlation KARTHIKEYA TSVR , for cross-correlation , you can refer this -- th-cam.com/video/xS8x6oAeg_U/w-d-xo.html Happy Learning
I believe the contents of this clip is good, however you talk in the "fast and furious" manner, make it hardly understandable, deviate the purpose of making it.
Code :
clc
clear all
close all
x=input('Enter the sequence');
n1=input('Enter the time sample range:');
h=fliplr(x);
n2=-fliplr(n1);
z=[];
for i=1:length(x)
g=h.*x(i);
z=[z;g];
end
[r c]=size(z);
k=r+c;
t=2;
y=[];
cd=0;
while(t
Thank you so much. It is really appreciated.
You are very welcome Josh H! Happy Learning :-)
Thank you! Much helpful explanation.
Glad it was helpful!
what if we have two inputs given ??
Then in that case , it is cross-correlation KARTHIKEYA TSVR , for cross-correlation , you can refer this -- th-cam.com/video/xS8x6oAeg_U/w-d-xo.html Happy Learning
could you pls explain on Wiener-Khintchine relation using power spectrum of given signal
Thank you so much
You're most welcome :-)
I believe the contents of this clip is good, however you talk in the "fast and furious" manner, make it hardly understandable, deviate the purpose of making it.
Thankyou so much.
You're most welcome Vaidehi Singh! Happy Learning :-)