Formula for number of unknown weights in Recurrent Neural Network
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Given a recurrent neural network with two hidden layers, with "I" represent the number of features of inputs, "O" represent the number of outputs. H1 and H2 represent the number hidden neurons in layer 1 and 2. What will be the formula for number of synaptic connections in Recurrent Neural Networks in terms of I, O, H1 and H2.
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Greg Heath
el 8 de En. de 2016
Editada: Greg Heath
el 8 de En. de 2016
I. Be specific:
MATLAB Version: 8.3.0.532 (R2014a)
Neural Network Toolbox Version 8.2 (R2014a)
>> lookfor recurrent
layrecnet - Layered recurrent neural network.
newhop - Design a Hopfield recurrent network.
newlrn - Create a Layered-Recurrent network.
II. Why don't you consider layrecnet and newlrn
A. Read the help documentation
B. Read the doc documentation
C. Modify the corresponding code examples
1. net1 with H2=0
2. Consider view(net1)and
Nw1 = net1.numWeightElements
3. Repeat 1 and 2 for net2 with H2~=0
III. I will compare my results with yours
Have fun,
Greg
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