Signal auto-correlation in matlab (xcorr function)

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Panos Kerezoudis
Panos Kerezoudis 2023-4-20
回答： Md Hasem 2024-10-25
Hi!
I am working on an EEG-electrophysiology dataset ('csd'). It is structured as a 3D array (channels x time x trials). The dimensions are 16x1527x200.
I am trying to calculate trial-averaged autocorrelation for each channel and I am getting the error message below. I think it has to do with the last part of my loop? The dimensions of the ac0 output (dot products) are 1x201 for some reason, I think the way the function is built, it adds one more column?
Any help would be great!
  2 个评论
Mathieu NOE
Mathieu NOE 2023-4-20
if you expect someone to help you , it's good practice to share some code and data
Panos Kerezoudis
Panos Kerezoudis 2023-4-20
Absolutely. The code is below. I cannot share data unfortunately (confidentiality reasons).
% Calculate trial-averaged auto-correlation
nchan = size(csd, 1); % channels
ntrials = size(csd, 3); % trials
nlags = 100; % n of lags
ac = zeros(1, 2*nlags + 1); % initialize auto-correlation vector
for i = 1:nchan % loop over channels
for k = 1:ntrials % loop over trials
x = csd(i, :, k) - mean(csd(i, :, k)); % mean-normalize data
[acO, lags] = xcorr(x, nlags, 'biased'); % biased estimate
ac(i, :) = ac(i, :) + double(acO(i, :)/ntrials); % add to total scaled by 1/k
end
end

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采纳的回答

Chunru
Chunru 2023-4-21
csd = randn(4, 100, 20); % dummy data
% Calculate trial-averaged auto-correlation
nchan = size(csd, 1); % channels
ntrials = size(csd, 3); % trials
nlags = 100; % n of lags
ac = zeros(nchan, 2*nlags + 1); % initialize auto-correlation vector
% ^^^^
for i = 1:nchan % loop over channels
for k = 1:ntrials % loop over trials
x = csd(i, :, k) - mean(csd(i, :, k)); % mean-normalize data
[acO, lags] = xcorr(x, nlags, 'biased'); % biased estimate
ac(i, :) = ac(i, :) + double(acO/ntrials); % add to total scaled by 1/k
% ^^^
end
end

更多回答（1 个）

Md Hasem
Md Hasem 2024-10-25
Read the Sun activity data from file sunspot.dat; 2. Filter the continuous component of the signal (centering the signal or using high-pass filter); 3. Calculate autocorrelation of the signal

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