LSTM Input Size Problem
Hello, I am attempting to train a LSTM network, but I'm struggling to resize the input data to the requirements of the LSTM. · LSTM Requirements: Nx1 - where N is the number of observations · My current data: XTrain, a 4D array (BxHxCxR) where: (Number of bands)-by-(Number of hops)-by-(Number of channels)-by-(Number of Responses) I want to create a column vector (Nx1), where each element of the vector has a 3D array (BxHxC) inside. My current code for resizing the data is the following: numResponses = size(xTrain,4); % Number of training samples for i = 1:numResponses xTrainReshaped(:,i) = xTrain(:,:,:,i); % EACH AUDIO has size of 128x42x2channels end yTrain = categorical(yTrain); % CATEGORICAL, N x 1 size ERROR: Unable to perform assignment because the size of the left side is 1-by-1 and the size of the right side is 128-by-42-by-2. What am I missing here? Some help would be certainly appreciated.
John Michell answered .
2025-11-20
%% RESHAPE INPUT DATA
% TRAIN DATA - MUST BE CHANGED TO: Nx1 - Where n is nTrainSamples
for i = 1:nTrainSamples
sampleTrain=xTrain(:,:,:,i);
xTrainReshaped{i} = sampleTrain;
end
xTrainReshaped = reshape(xTrainReshaped,[nTrainSamples 1]); % Create a column vector
yTrain = categorical(yTrain);
% CONVERT TEST DATA INTO Nx1
nTestSamples = size(xTest,4);
for i = 1:nTestSamples
sampleTest=xTest(:,:,:,i);
xTestReshaped{i} = sampleTest;
end
xTestReshaped = reshape(xTestReshaped,[nTestSamples 1]); % Create a column vector
yTest = categorical(yTest);