You can combine 3 separate LSTM-s into one network by adding them to a dlnetwork object and hooking up the outputs. Note that if the LSTM-s have OutputMode="sequence" then either you need all input sequences to have the same length, or have some layer(s) that can manage the data with different sequence lengths.
Here's an example with OutputMode="last"
inputSizes = [1,2,3];
outputSize = 4;
lstmHiddenSize = 5;
hiddenSize = 10;
sequenceLengths = [6,7,8];
x1 = dlarray(rand(inputSizes(1),sequenceLengths(1)),"CT");
x2 = dlarray(rand(inputSizes(2),sequenceLengths(2)),"CT");
x3 = dlarray(rand(inputSizes(3),sequenceLengths(3)),"CT");
layers = [
sequenceInputLayer(inputSizes(1))
lstmLayer(lstmHiddenSize,OutputMode="last")
concatenationLayer(1,3,Name="cat")
fullyConnectedLayer(hiddenSize)
reluLayer
fullyConnectedLayer(outputSize)];
net = dlnetwork(layers,Initialize=false);
net = addLayers(net,[sequenceInputLayer(inputSizes(2));lstmLayer(lstmHiddenSize,OutputMode="last",Name="lstm2")]);
net = addLayers(net,[sequenceInputLayer(inputSizes(3));lstmLayer(lstmHiddenSize,OutputMode="last",Name="lstm3")]);
net = connectLayers(net,"lstm2","cat/in2");
net = connectLayers(net,"lstm3","cat/in3");
net = initialize(net);
y = predict(net,x1,x2,x3)
