/// <summary>
/// Clone this object.
/// </summary>
/// <returns>A clone of this object.</returns>
public override object Clone()
{
WeightedSynapse result = new WeightedSynapse();
result.WeightMatrix = (Matrix)this.WeightMatrix.Clone();
return(result);
}
/// <summary>
/// Load the specified Encog object from an XML reader.
/// </summary>
/// <param name="xmlIn">The XML reader to use.</param>
/// <returns>The loaded object.</returns>
public IEncogPersistedObject Load(ReadXML xmlIn)
{
WeightedSynapse synapse = new WeightedSynapse();
String end = xmlIn.LastTag.Name;
while (xmlIn.ReadToTag())
{
if (xmlIn.IsIt(WeightedSynapsePersistor.TAG_WEIGHTS, true))
{
xmlIn.ReadToTag();
synapse.WeightMatrix = PersistorUtil.LoadMatrix(xmlIn);
}
if (xmlIn.IsIt(end, false))
{
break;
}
}
return synapse;
}
/// <summary>
/// Clone this object.
/// </summary>
/// <returns>A clone of this object.</returns>
public override object Clone()
{
WeightedSynapse result = new WeightedSynapse();
result.WeightMatrix = (Matrix)this.WeightMatrix.Clone();
return result;
}
/// <summary>
/// Add a "next" layer.
/// </summary>
/// <param name="next">The next layer to add.</param>
/// <param name="type">The synapse type to use for this layer.</param>
public void AddNext(ILayer next, SynapseType type)
{
ISynapse synapse = null;
switch (type)
{
case SynapseType.OneToOne:
synapse = new OneToOneSynapse(this, next);
break;
case SynapseType.Weighted:
synapse = new WeightedSynapse(this, next);
break;
case SynapseType.Weightless:
synapse = new WeightlessSynapse(this, next);
break;
case SynapseType.Direct:
synapse = new DirectSynapse(this, next);
break;
case SynapseType.NEAT:
synapse = new NEATSynapse(this, next);
break;
default:
throw new NeuralNetworkError("Unknown synapse type");
}
if (synapse == null)
{
String str = "Unknown synapse type.";
#if logging
if (BasicLayer.logger.IsErrorEnabled)
{
BasicLayer.logger.Error(str);
}
#endif
throw new NeuralNetworkError(str);
}
else
{
this.next.Add(synapse);
}
}
/// <summary>
/// The generated network.
/// </summary>
/// <returns></returns>
public BasicNetwork Generate()
{
BasicNetwork network = new BasicNetwork(new BAMLogic());
ILayer f1Layer = new BasicLayer(new ActivationBiPolar(), false,
F1Neurons);
ILayer f2Layer = new BasicLayer(new ActivationBiPolar(), false,
F2Neurons);
ISynapse synapseInputToOutput = new WeightedSynapse(f1Layer,
f2Layer);
ISynapse synapseOutputToInput = new WeightedSynapse(f2Layer,
f1Layer);
f1Layer.AddSynapse(synapseInputToOutput);
f2Layer.AddSynapse(synapseOutputToInput);
network.TagLayer(BAMPattern.TAG_F1, f1Layer);
network.TagLayer(BAMPattern.TAG_F2, f2Layer);
network.Structure.FinalizeStructure();
network.Structure.FinalizeStructure();
f1Layer.Y = PatternConst.START_Y;
f2Layer.Y = PatternConst.START_Y;
f1Layer.X = PatternConst.START_X;
f2Layer.X = PatternConst.INDENT_X;
return network;
}
/// <summary>
/// Generate the neural network.
/// </summary>
/// <returns>The generated neural network.</returns>
public BasicNetwork Generate()
{
BasicNetwork network = new BasicNetwork(new ART1Logic());
int y = PatternConst.START_Y;
ILayer layerF1 = new BasicLayer(new ActivationLinear(), false, this.InputNeurons);
ILayer layerF2 = new BasicLayer(new ActivationLinear(), false, this.OutputNeurons);
ISynapse synapseF1toF2 = new WeightedSynapse(layerF1, layerF2);
ISynapse synapseF2toF1 = new WeightedSynapse(layerF2, layerF1);
layerF1.Next.Add(synapseF1toF2);
layerF2.Next.Add(synapseF2toF1);
// apply tags
network.TagLayer(BasicNetwork.TAG_INPUT, layerF1);
network.TagLayer(BasicNetwork.TAG_OUTPUT, layerF2);
network.TagLayer(ART1Pattern.TAG_F1, layerF1);
network.TagLayer(ART1Pattern.TAG_F2, layerF2);
layerF1.X = PatternConst.START_X;
layerF1.Y = y;
y += PatternConst.INC_Y;
layerF2.X = PatternConst.START_X;
layerF2.Y = y;
network.SetProperty(ARTLogic.PROPERTY_A1, this.A1);
network.SetProperty(ARTLogic.PROPERTY_B1, this.B1);
network.SetProperty(ARTLogic.PROPERTY_C1, this.C1);
network.SetProperty(ARTLogic.PROPERTY_D1, this.D1);
network.SetProperty(ARTLogic.PROPERTY_L, this.L);
network.SetProperty(ARTLogic.PROPERTY_VIGILANCE, this.Vigilance);
network.Structure.FinalizeStructure();
return network;
}
