/*public vNeuron(main.Network inNet, List<List<int>> inInputNs, int inLayer, int inDim)
* {
* this.inputNeurons = inInputNs;
* this.layer = inLayer;
* this.dimension = inDim;
*
* this.weights = new List<List<double>>();
* for(int i = 0; i < inNet.NUM_DEPTH; i++)
* {
* this.weights.Add(Enumerable.Repeat(DEFAULT_WEIGHT, inDim).ToList());
* }
* }*/
//Input Neuron Constructor
public vNeuron(List <double> output)
{
this.layer = 0;
this.actFunc = actFuncType.identity;
this.dimension = output.Count;
this.inputs.Add(new List <double>());
for (int i = 0; i < this.dimension; i++)
{
this.inputs[0].Add(output[i]);
this.beta.Add(0d);
}
this.weights.Add(MyMath.makeIdentityMatrix(this.dimension));
}
//Input Neuron Constructor
public mNeuron(List <List <double> > output)
{
this.layer = 0;
this.actFunc = actFuncType.identity;
int d = 0;
this.inputs.Add(new List <List <double> >());
for (int i = 0; i < output.Count; i++)
{
d++;
this.inputs[0].Add(new List <double>());
this.beta.Add(new List <double>());
for (int j = 0; j < output[0].Count; j++)
{
this.inputs[0][i].Add(output[i][j]);
this.beta[i].Add(0d);
}
}
this.weights.Add(MyMath.makeIdentityMatrix(d));
}
