I have a cell array with vectors y1, y2, y3, y4, y5 which are of variable lengths. I get the maximum length among all elements in the cell array using:
sigvecarray = {y1, y2, y3, y4, y5}; [maxsamples, idx] = max(cellfun(@numel, sigvecarray));
signalvectors = {} for k = 1:numel(sigvecarray) currveclength = length(sigvecarray{k}) if currveclength < maxsamples padding = samples - currveclength signalvectors{k} = [sigvecarray{k}, zeros(padding, 1)] end end
Error using horzcat Dimensions of matrices being concatenated are not consistent.
Then I tried the solution from the post here as follows:
origsamplesarray = cellfun(@numel, sigvecarray); padfun = @(k) [sigvecarray{k} zeros(maxsamples(k) - origsamplesarray(k), 1)] ; signalvectors = arrayfun(padfun, 1:numel(sigvecarray) , 'un', 0);
It gave me the following error:
Error using horzcat Dimensions of matrices being concatenated are not consistent. Error in xcorr>@(k)[sigvecarray{k},zeros(maxsamples(k)-origsamplesarray(k),1)]
What am I possibly doing wrong above?
signalvectors{k} = [sigvecarray{k}; zeros(padding, 1)]
All of these — including this:
padfun = @(k) [sigvecarray{k} zeros(maxsamples(k) - origsamplesarray(k), 1)] ;
function — are concatenating something with a column vector, that column vector being defined as:
zeros(maxsamples(k) - origsamplesarray(k), 1)
padfun = @(k) [sigvecarray{k}; zeros(maxsamples(k) - origsamplesarray(k), 1)] ; ↑ ← VERTICAL CONCATENATION OPERATOR
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