How can I split my dataset in training/validation/test set when the dataset is a cell array?

I am training an Elman network and for that reason my datasets (input/target) need to be cell arrays (so that the examples are considered as a sequence by the train function).

But, I don't manage to trigger the use of a validation and test set by the train function.

Here is an example, where I want a validation and test set to be used but the train function is not using any. It seems the "divideind" property and indexes are ignored.

%%Set the parameters of the run
n_neurons = 50;         % Number of neurons
n = 1000;               % Total number of samples
ne = 500;               % Number of epochs

%%Create the samples
% Allocate memory
u = zeros(1, n);
x = zeros(1, n);
y = zeros(1, n);

% Initialize u, x and y
u(1)=randn; 
x(1)=rand+sin(u(1));
y(1)=x(1);

% Calculate the samples
for i=2:n
    u(i)=randn;
    x(i)=.8*x(i-1)+sin(u(i));
    y(i)=x(i);
end

%%Create the datasets
X=num2cell(u); 
T=num2cell(y);

%%Train and simulate the network
% Create the net and apply the selected parameters
net = newelm(X,T,n_neurons);        % Create network
net.trainParam.epochs = ne;         % Number of epochs

net.divideFcn = 'divideind';
net.divideParam.trainInd = 1:800;
net.divideParam.valInd = 801:900;
net.divideParam.testInd = 901:1000;

[net,tr]= train(net,X,T);

Answer 1

[Thomas Laurent]

I found the answer, I need to add:

net.divideMode = 'time';

so that cell arrays can be divided in train/validation/test sets, for example with:

net.divideFcn = 'divideind';