public void SetActivationFunction(NeuralActivationFunction _neuralActivationFunction)
{
switch (_neuralActivationFunction)
{
case NeuralActivationFunction.Sigmoid:
actFunction = ActivationFunctions.Sigmoid;
actFunctionDer = ActivationFunctions.SigmoidDer;
break;
case NeuralActivationFunction.Tanh:
actFunction = ActivationFunctions.Tanh;
actFunctionDer = ActivationFunctions.TanhDer;
break;
case NeuralActivationFunction.Relu:
actFunction = ActivationFunctions.Relu;
actFunctionDer = ActivationFunctions.ReluDer;
break;
case NeuralActivationFunction.LeakyRelu:
actFunction = ActivationFunctions.LeakyRelu;
actFunctionDer = ActivationFunctions.LeakyReluDer;
break;
default:
break;
}
}
public Neuron(NeuralActivationFunction _neuralActivationFunction)
{
inputSynapses = new List <Synapse>();
outputSynapses = new List <Synapse>();
SetActivationFunction(_neuralActivationFunction);
bias = NeuralNetwork.GetRandom();
}
public NeuralGeneNode(NeuralActivationFunction _neuralActivationFunction, int _nodeNumber, NeuralNodeType _nodeType)
{
inputSynapses = new List <NeuralGeneConnection>();
outputSynapses = new List <NeuralGeneConnection>();
SetActivationFunction(_neuralActivationFunction);
nodeNumber = _nodeNumber;
nodeType = _nodeType;
bias = NeatNeuralNetwork.GetRandom();
}
public Neuron(NeuralActivationFunction _neuralActivationFunction, IEnumerable <Neuron> _inputNeurons)
{
inputSynapses = new List <Synapse>();
outputSynapses = new List <Synapse>();
SetActivationFunction(_neuralActivationFunction);
bias = NeuralNetwork.GetRandom();
foreach (var inputNeuron in _inputNeurons)
{
var synapse = new Synapse(inputNeuron, this);
inputNeuron.outputSynapses.Add(synapse);
inputSynapses.Add(synapse);
}
}
public NeuralGeneNode AddHiddenNode(NeuralActivationFunction _neuralActivationFunctions)
{
if (HiddenLayers == null)
{
HiddenLayers = new List <NeuralGeneNode>();
}
if (nodes == null)
{
nodes = new List <NeuralGeneNode>();
}
NeuralGeneNode tmpNode = new NeuralGeneNode(_neuralActivationFunctions, nodes.Count + 1, NeuralNodeType.Hidden);
HiddenLayers.Add(tmpNode);
nodes.Add(tmpNode);
return(tmpNode);
}
public NeuralGeneNode AddOutputNode(NeuralActivationFunction _neuralActivationFunctions)
{
if (OutputLayer == null)
{
OutputLayer = new List <NeuralGeneNode>();
}
if (nodes == null)
{
nodes = new List <NeuralGeneNode>();
}
NeuralGeneNode tmpNode = new NeuralGeneNode(_neuralActivationFunctions, nodes.Count + 1, NeuralNodeType.Output);
OutputLayer.Add(tmpNode);
nodes.Add(tmpNode);
return(tmpNode);
}
public void AddInputsNode(int _inputSize, NeuralActivationFunction _neuralActivationFunctions)
{
if (InputLayer == null)
{
InputLayer = new List <NeuralGeneNode>();
}
if (nodes == null)
{
nodes = new List <NeuralGeneNode>();
}
for (int i = 0; i < _inputSize; i++)
{
NeuralGeneNode tmpNode = new NeuralGeneNode(_neuralActivationFunctions, i + 1, NeuralNodeType.Input);
InputLayer.Add(tmpNode);
nodes.Add(tmpNode);
}
}
public void AddOutputsNode(int _outputSize, NeuralActivationFunction _neuralActivationFunctions)
{
if (OutputLayer == null)
{
OutputLayer = new List <NeuralGeneNode>();
}
if (nodes == null)
{
nodes = new List <NeuralGeneNode>();
}
for (int i = 0; i < _outputSize; i++)
{
NeuralGeneNode tmpNode = new NeuralGeneNode(_neuralActivationFunctions, nodes.Count + 1, NeuralNodeType.Output);
OutputLayer.Add(tmpNode);
nodes.Add(tmpNode);
}
}
