public List <NeuralPathway> GetPathways(Dynamic o)
{
var pathways = new List <NeuralPathway>();
var path = new NeuralPathway();
path.Path.Add(o);
path.Weightings.Add(1);
var paths = o.ExtendPathway(path);
pathways.AddRange(paths);
return(pathways);
}
public NeuralPathway Copy()
{
var copy = new NeuralPathway();
foreach (var p in Path)
{
copy.Path.Add(p);
}
foreach (var w in Weightings)
{
copy.Weightings.Add(w);
}
return(copy);
}
public override double GetOutput(NeuralPathway path = null)
{
if (path != null)
{
if (path.Path.Count(Equivelant) > 2)
{
return(0);
}
path.Path.Add(this);
}
var sum = Dendrites.Aggregate <Dendrite, double>(0, (current, d) => current + (d.GetSignal(path)));
return(Function(sum));
}
/**
* backpropagate
* sends weighted error back through the network
* re-weights input based on error.
* @param error (double)
*/
public override void Backpropagate(double error, NeuralPathway path = null)
{
if (path != null)
{
if (path.Path.Count(Equivelant) > 2)
{
return;
}
path.Path.Add(this);
}
//http://home.agh.edu.pl/~vlsi/AI/backp_t_en/backprop.html
foreach (var d in Dendrites)
{
d.Neuron.Backpropagate(error * d.Weight, path);
Reweight(d, error, path);
}
}
public IEnumerable <NeuralPathway> ExtendPathway(NeuralPathway pathway)
{
var pathways = new List <NeuralPathway>();
if (Dendrites.Count <= 0)
{
return new List <NeuralPathway>()
{
pathway
}
}
;
foreach (var d in Dendrites)
{
var path = pathway.Copy();
path.Path.Add(d.Neuron);
path.Weightings.Add(d.Weight);
var paths = d.Neuron.ExtendPathway(path);
pathways.AddRange(paths);
}
return(pathways);
}
}
/**
* reweight
* Sets the weight of the given dendrite based on its error.
* @param dendrite (Dendrite) to be reweighted
* @param error (double)
*/
private void Reweight(Dendrite dendrite, double error, NeuralPathway path = null)
{
var weight = dendrite.Weight + LearningRate * error * Derivative(GetOutput(path)) * dendrite.Neuron.GetOutput(path);
dendrite.Weight = weight;
}
/** * backpropagate * all nodes must backpropagate errors * @param error (double) */ public abstract void Backpropagate(double error, NeuralPathway path = null);
/** * getOutput * Abstract, all nodes must return an output * @return double value */ public abstract double GetOutput(NeuralPathway path = null);
/**
* backpropagate
* Static neurons do not need to backpropagate
*/
public override void Backpropagate(double error, NeuralPathway path = null)
{
}
/**
* getOutput
* Static INeurons return their value
* @return double value
*/
public override double GetOutput(NeuralPathway path = null)
{
return(Value);
}
public double GetWeightedOutput(NeuralPathway path = null)
{
return(Weight * Neuron.GetOutput(path));
}
public double GetSignal(NeuralPathway path = null)
{
return(GetWeightedOutput(path));
}
