private double DeltaHidden(CNeuronWithSynapse neuron, double delta)
{
double deltaHidden = DerivativeSigmoid(neuron.GetValue());
double sum = 0;
for (int i = 0; i < neuron.GetSynapses().Count; ++i)
{
sum += (neuron.GetCertainSynapse(i) * delta);
}
deltaHidden *= sum;
return(deltaHidden);
}
public void Create(string name, int inputCount, int hiddenCount, int outputCount)
{
jsonCommander = new JsonCommander();
m_name = name;
for (int i = 0; i < inputCount; ++i)
{
CNeuronWithSynapse inputNeuron = new CNeuronWithSynapse(0, CreateRandomList(hiddenCount));
m_InputNeurons.Add(inputNeuron);
}
for (int i = 0; i < hiddenCount; ++i)
{
CNeuronWithSynapse hiddenNeuron = new CNeuronWithSynapse(0, CreateRandomList(outputCount));
m_HiddenNeurons.Add(hiddenNeuron);
}
for (int i = 0; i < outputCount; ++i)
{
CNeuron outputNeuron = new CNeuron(0);
m_OutputNeurons.Add(outputNeuron);
}
if (File.Exists(m_name + ".json"))
{
JsonData[] synapses = jsonCommander.DeSerialize(m_name);
for (int i = 0; i < m_InputNeurons.Count; ++i)
{
for (int j = 0; j < m_HiddenNeurons.Count; ++j)
{
m_InputNeurons[i].SetСertainOutSynape(j, synapses[0].m_values[i][j]);
}
}
for (int i = 0; i < m_HiddenNeurons.Count; ++i)
{
for (int j = 0; j < m_OutputNeurons.Count; ++j)
{
m_HiddenNeurons[i].SetСertainOutSynape(j, synapses[1].m_values[i][j]);
}
}
}
System.Console.WriteLine("Neural Network is initialized");
//Print("After Create");
}