You can access the layer weights as follows:
net.LW{i,j}
You can set any values to the above weights and set the net.layerWeights{i,j}.learn to 0 so that the weights won't be altered during the training & adaption. In this case setting a specific weight for a connection is not possible since the property net.layerWeights{i,j}.learn is defined for the entire connections between layers i and j.
net.layerWeights{i,j}.learn = 0
net.LW{i,j} = ones(size(net.LW{i,j})) % any weights of size(net.LW{i,j})
If your network architecture is defined and trained already:
Then you can set weight of a connection between nodes k & l of layers i & j as follows:
net.LW{i,j}(k,l) = 1
and then use the network.
The above things can be done to Input wieghts too.
