/// <summary>
/// Creates an instance of CompetitiveNeuron with specified input and transfer functions
/// </summary>
/// <param name="inputFunction">neuron input function</param>
/// <param name="transferFunction">neuron ransfer function</param>
public CompetitiveNeuron(InputFunction inputFunction, TransferFunction transferFunction)
: base(inputFunction, transferFunction)
{
connectionsFromOtherLayers = new List<Connection>();
connectionsFromThisLayer = new List<Connection>();
this.AddInputConnection(this, 1);
}
/// <summary>
/// Creates an instance of neuron which can delay output
/// </summary>
/// <param name="inputFunction">neuron input function</param>
/// <param name="transferFunction">neuron transfer function</param>
public DelayedNeuron(InputFunction inputFunction,
TransferFunction transferFunction)
: base(inputFunction, transferFunction)
{
outputHistory = new List<Double>(5); // default delay buffer size is 5
outputHistory.Add(0);
}
/// <summary>
/// Creates and returns neuron instance according to the given specification in neuronProperties.
/// </summary>
/// <param name="neuronProperties">specification of neuron properties</param>
/// <returns>returns instance of neuron with specified properties</returns>
public static Neuron CreateNeuron(NeuronProperties neuronProperties)
{
InputFunction inputFunction = null;
Type inputFunctionClass = neuronProperties.InputFunction;
if (!inputFunctionClass.Equals(" "))
{
inputFunction = CreateInputFunction(inputFunctionClass);
}
else
{
WeightsFunction weightsFunction = CreateWeightsFunction(neuronProperties.WeightsFunction);
SummingFunction summingFunction = CreateSummingFunction(neuronProperties.SummingFunction);
inputFunction = new InputFunction(weightsFunction, summingFunction);
}
TransferFunction transferFunction = CreateTransferFunction(neuronProperties.GetTransferFunctionProperties());
Neuron neuron = null;
Type neuronClass = neuronProperties.NeuronType;
// use two param constructor to create neuron
Type[] paramTypes = {
typeof(InputFunction),
typeof(TransferFunction) };
ConstructorInfo con = neuronClass.GetConstructor(paramTypes);
if (con != null)
{
Object[] paramList = new Object[2];
paramList[0] = inputFunction;
paramList[1] = transferFunction;
object o = con.Invoke(paramList);
neuron = (Neuron)o;
}
if (neuron == null)
{
neuron = (Neuron)Activator.CreateInstance(neuronClass);
}
if (neuronProperties.HasProperty("thresh"))
{
((ThresholdNeuron)neuron).Thresh = ((Double)neuronProperties.GetProperty("thresh"));
}
else if (neuronProperties.HasProperty("bias"))
{
((InputOutputNeuron)neuron).Bias = ((Double)neuronProperties.GetProperty("bias"));
}
return neuron;
}
/// <summary>
/// Creates a neuron with threshold behaviour, and with the specified input
/// and transfer functions.
/// </summary>
/// <param name="inputFunction">input function for this neuron</param>
/// <param name="transferFunction">transfer function for this neuron</param>
public ThresholdNeuron(InputFunction inputFunction, TransferFunction transferFunction)
{
this.InputFunction = inputFunction;
this.TransferFunction = transferFunction;
this.Thresh = ThreadSafeRandom.NextDouble();
}
/// <summary>
/// Creates an instance of neuron for Hopfield network with specified input
/// and transfer functions
/// </summary>
/// <param name="inFunc">neuron input function</param>
/// <param name="transFunc">neuron transfer function</param>
public InputOutputNeuron(InputFunction inFunc, TransferFunction transFunc)
: base(inFunc, transFunc)
{
}
/// <summary>
/// Creates an instance of Neuron with the specified input and transfer functions.
/// </summary>
/// <param name="inputFunction">input function for this neuron</param>
/// <param name="transferFunction">transfer function for this neuron</param>
public Neuron(InputFunction inputFunction, TransferFunction transferFunction)
{
this.InputFunction = inputFunction;
this.TransferFunction = transferFunction;
}
