Hello, I had a Elman network with 3 hidden layers, 3 input layers and 1 output layer. I try to initial the hidden layer weights with a decent trained result which is saved before. But when I re-input the hidden layer weights into the network. Errors always bumped out. Error:net.LW{2,1} must be a 0-by-3 matrix. The error also happened when I valued the bias and input layer weights. I have two questions: (1) What does "0-by-3 matrix" mean? Does it mean the matrix should be a empty matrix? (2) I got the hidden layer weights, input layer weights and bias from the trainning result. Why it doesn't work when I re-input them into the network? They were saved in ".mat" format. They were all "cell" structure.
*
iw = net.iw;
lw = net.lw;
theta = net.b;
*
net.b{1} = theta{1,1};
net.lw{2,1} = lw{2,1};
net.iw{1,1} = iw{1,1};
net.b{2} = theta{2,1};
>> net.lw{2,1}
ans =
>> lw{2,1} % saved trainning result of hidden layer weight (variable "lw")
ans =
>> net.iw{1,1}
ans =
>> iw{1,1} % saved trainning result of input layer weight (variable "iw")
ans =
0.7936 0.7638 0.6892
-0.0306 -0.3250 -0.0438
0.8408 -1.0601 -0.9286
*
Error: network/subsasgn>network_subsasgn (line 553)
net.LW{2,1} must be a 0-by-3 matrix.
Error: network/subsasgn (line 13)
net = network_subsasgn(net,subscripts,v,netname);
Error: elman_PepperHTHS_v2 (line 65)
net.lw{2,1} = lw{2,1};
*
I can value net.b{1} successfuly but not the other three. That confused me a lot. If it could be answered, that would be appreciated so much.
