Matlab Neural Network Structure

Question

I'm full newbie in neural networks. I generated NN in matlab. Further I need to know exact structure of this NN, because I need to implement it in Java(static connections and weights, no learning). Can you explain how to connect neurons and what math operations perform in each element?

NN params are next(taken from Matlab):

iw{1,1} - Weight to layer 1 from intput 1

[2.8574 -1.9207;
 1.7582 -1.2549;
 -4.5925 0.23236;
 12.0861 12.3701;
 2.503 -1.9321;
 -2.1422 2.6928]

lw{2,1} - Weight to layer

[-0.51977 5.3993 3.4349 5.2863 3.1976 -0.67102]

b{1} - Bias to layer 1

[-3.2811;
 -6.956;
 -3.0943;
 11.1103;
 0.14842;
 -3.3705]

b{2} - Bias to layer 2

[1.4657]

Transfer function TANSIG Greatly appreciate your help.

Answer 1

You have a NN that has 2 inputs, then a hidden layer of 6 neurons and an output layer of 1 neuron.

Each of the neuron in each layer, will take all the outputs from the previous one and multiply them by a number and offset the result by another.

The numbers you show are the numbers I mentioned.

For example, the neuron 1 from hidden layer will output hidden1=2.8574*in1 -1.9207*in2-3.2811 . Then take whatever sigma function you are using and apply hidden1=sigma(hidden1) .

As another example, the output will be out=-hidden1*0.51977+hidden2*5.3993+...-hidden6*0.67102+1.4657