public override void InitializeNetwork()
{
//
m_Layers = new ANNLayer[m_Parameters.m_NumHiddenLayers + 1];
//create neurons in hidden layers
for (int i = 0; i < m_Parameters.m_NumHiddenLayers; i++)
{
if (i == 0)
{
m_Layers[i] = new ANNLayer(m_InputCount, m_Parameters.m_NeuronsInHiddenLayer, m_Parameters.m_ActFunction);
}
else
{
m_Layers[i] = new ANNLayer(m_Parameters.m_NeuronsInHiddenLayer, m_Parameters.m_NeuronsInHiddenLayer, m_Parameters.m_ActFunction);
}
}
//create neurons and error array for the last layer, which is usualy 1
m_Layers[m_Parameters.m_NumHiddenLayers] = new ANNLayer(m_Parameters.m_NeuronsInHiddenLayer, m_OutputCount, m_Parameters.m_ActFunction);
}
public override void InitializeNetwork()
{
//
m_Layers = new Layer[m_Parameters.m_NumHiddenLayers + 1];
//create neurons in hidden layers
for (int i = 0; i < m_Parameters.m_NumHiddenLayers; i++)
{
if (i == 0)
{
m_Layers[i] = new ANNLayer(m_InputCount, m_Parameters.m_NeuronsInHiddenLayer, m_Parameters.m_ActFunction);
}
else
{
m_Layers[i] = new ANNLayer(m_Parameters.m_NeuronsInHiddenLayer, m_Parameters.m_NeuronsInHiddenLayer, m_Parameters.m_ActFunction);
}
}
//create neurons array for the last layer, with logistic Sigfmoid activation
Layer ly = new ANNLayer(m_Parameters.m_NeuronsInHiddenLayer, m_OutputCount, new Sigmoid(1.0));
m_Layers[m_Parameters.m_NumHiddenLayers] = ly;
}
