MATLAB Answers

autocorrelate rows of matrix without using a for loop

20 views (last 30 days)
Cody
Cody on 25 Aug 2011
Hello, can anyone help me to write 'vectorized' code to compute the autocorrelation of each row of a matrix without using a for loop? My current code computes the autocorrelation of the rows like this:
for m=1:10
b(m,:)=xcorr( a(m,:) );
end
This is slow and inefficient. There must be a better way? Thanks, -Cody

Answers (6)

Rick Rosson
Rick Rosson on 25 Aug 2011
Hi Cody,
Can you please answer the following questions?
  1. Did you pre-allocate the output array b ?
  2. Also, have you considered that MATLAB stores arrays column-major, so that your code might be faster and more efficient if you used the transpose of a, even though it is still in a for loop?
Thanks!
Rick

Sean de Wolski
Sean de Wolski on 25 Aug 2011
for m=10:-1:1
b(m,:)=xcorr( a(m,:) );
end
  5 Comments

Sign in to comment.


Rick Rosson
Rick Rosson on 25 Aug 2011
Also, please check the documentation for xcorr:
>> doc xcorr
It looks like you may be able to accomplish what you want without a for loop if you first transpose a and then consider each column of a as an independent channel.
HTH.
Rick
  1 Comment
Cody
Cody on 25 Aug 2011
Rick, thanks for the response. Yes, I have preallocated the output array. I will also transpose the array before calling xcorr() and see if that makes much of a difference, however, my intuition tells me that there is probably a clever way to accomplish this calculation without using a for loop. I've also noticed that cov() or xcov() won't operate on individual rows or columns separately and I find it hard to believe that Mathworks simply overlooked such functionality.
The problem I see with the channel method you mentioned is that the output produces the autocorrelation of each column along with the cross-correlation of each column with every other column. This results in large matrices and lots of wasted output data because I'm only interested in the autocorrelation of each row and not the cross-correlation between the rows.

Sign in to comment.


Honglei Chen
Honglei Chen on 25 Aug 2011
You can use FFT if your data is large, e.g.,
ffta = fft(a,NFFT,2);
b = fftshift(ifft(ffta.*conj(ffta),[],2),2)
Choose your NFFT as 2*size(a,2)-1 to match xcorr behavior. You may gain even more if you can transpose your data first to make these function working along columns.
HTH
  2 Comments
Sebastian Holmqvist
Sebastian Holmqvist on 21 Mar 2013
This is actually what xcorr does. Just my two cents.

Sign in to comment.


Rick Rosson
Rick Rosson on 25 Aug 2011
Is the issue here that you really need to make this code run faster, or is it that you are just hoping to find a more elegant (e.g. vectorized) way to accomplish this task without resorting to a for loop?
How much time is it taking to run this code now? How fast do you need it to be?
  2 Comments

Sign in to comment.


Chaowei Chen
Chaowei Chen on 27 Aug 2011
The idea is to convert mat to cell since each row is independent. After processing, convert cell back to mat.
a2=mat2cell(a,ones(1,size(a,1)),size(a,2));
b2=cellfun(@xcorr,a2,'uniformoutput',false);
b2=cell2mat(b2);
isequal(b,b2)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!