public Neuron(List <double> weights, double bias, mathFunction activationFunction)
{
this.activationFunction = activationFunction;
this.init(weights.Count);
this.weights = weights;
this.bias = bias;
}
public Neuron(List<double> weights, double bias, mathFunction activationFunction)
{
this.activationFunction = activationFunction;
this.init(weights.Count);
this.weights = weights;
this.bias = bias;
}
/*Constructors*/
public Neuron(int numOfinput, mathFunction activationFunction,bool LMS)
{
this.activationFunction = activationFunction;
if (!LMS)
this.init(numOfinput);
else
this.initLMS(numOfinput);
}
// least mean square
public void LMSsetLayer(int layerIndex, mathFunction activationFunction)
{
if (layerIndex == 0)
throw new Exception("Can't set Input Layer");
for (int i = 0; i < this.numOfNeuronsPerLayer[layerIndex]; ++i)
{
Neuron neuron = new Neuron(this.numOfNeuronsPerLayer[layerIndex - 1], activationFunction,true);
this.network[layerIndex - 1].Add(neuron);
}
}
/*Constructors*/
public Neuron(int numOfinput, mathFunction activationFunction, bool LMS)
{
this.activationFunction = activationFunction;
if (!LMS)
{
this.init(numOfinput);
}
else
{
this.initLMS(numOfinput);
}
}
// least mean square
public void LMSsetLayer(int layerIndex, mathFunction activationFunction)
{
if (layerIndex == 0)
{
throw new Exception("Can't set Input Layer");
}
for (int i = 0; i < this.numOfNeuronsPerLayer[layerIndex]; ++i)
{
Neuron neuron = new Neuron(this.numOfNeuronsPerLayer[layerIndex - 1], activationFunction, true);
this.network[layerIndex - 1].Add(neuron);
}
}
