Formula for number of unknown weights in Recurrent Neural Network

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.

[Greg Heath]

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