How can I study Autocorrelation function of common inputs?

I'm trying to study the autocorrelation function for some basic signals, such as rectangularPulse and triangularPulse, and to do that I found the xcorr () function. The problem is that the function wants 2 vectors in input, so I'm trying to convert the function to vectors, but mine can be a non linear function...

Also I don't even know if this is the right way...

Everything I'm trying I found here https://en.mathworks.com/help/signal/correlation-and-convolution.html.

Answer 1

[Balaji Udayagiri]

Hi Teodoro,

As per my understanding, you want to know how to perform autocorrelation for non-linear functions.

You can use the xcorr() function to do the same.

Here is an example code using a sine function to do the same:

fs = 1.0e4; 
t = 0:1/fs:0.005; 
signal = sin(2*pi*1000*t)'; 
figure(1); 
stem(t,signal); 
[c,lags] = xcorr(signal); 
figure(2); 
stem(lags,c) 

You can replace the sin function of any linear or non-linear function of your choice.

Answer 2

[Jonas]

you can simply generate your own vectors in matlab and do some studying

e.g.

rectPulse = [zeros(1,10) ones(1,15) zeros(1,10)];

tiledlayout('flow');
nexttile()
stem(rectPulse);

nexttile()
[val,lag]=xcorr(rectPulse);
stem(lag,val);

linkaxes()

figure
triPulse=zeros(1,100);
triPulse(31:70)=(1:40)/10;

tiledlayout('flow');
nexttile()
plot(triPulse);

nexttile()
[val,lag]=xcorr(triPulse);
plot(lag,val);
nexttile()
val=conv(triPulse,triPulse);
plot(val);