public void PlugIn(List <Input> neurons)
{
foreach (var n in neurons)
{
var temp = n;
foreach (var d in Dendrites.Where(d => d.Neuron.Name == temp.Name))
{
d.Neuron = n;
}
}
}
public void ForceCreateDendrite(Neuron source, double strength)
{
if (DendriteStrength.ContainsKey(source))
{
DendriteStrength[source] = strength;
}
else
{
DendriteStrength.Add(source, strength);
Dendrites.Add(source);
source.Axons.Add(this);
}
}
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));
}
public void CountError(Layer layer)
{
List <double> all_multiplications = new List <double>();
foreach (var neuron in layer.Neurons)
{
if (neuron.Bias)
{
continue;
}
double weight = Dendrites
.SingleOrDefault(x => x.TargetNeuron == neuron.ID)
.Weight;
all_multiplications.Add(weight * neuron.ErrorSignal);
}
double result = Value * (1 - Value) * all_multiplications.Sum();
ErrorSignal = result;
}
public virtual void AddDendrites(List <Dendrite> dendrites)
{
Dendrites.AddRange(dendrites);
}
public virtual void AddDendrite(Dendrite dendrite)
{
Dendrites.Add(dendrite);
}
public virtual void Compute()
{
var sum = Dendrites.Sum(dendrite => dendrite.Value * dendrite.Weight);
Axon.Value = Activation(sum);
}
public int CountDendrites()
{
return(Dendrites.Count());
}
public void UpdateWeights(double new_weights)
{
Dendrites.ToList().ForEach(x => x.SynapticWeight = new_weights);
}
public void Calculate()
{
Value = Dendrites.Sum(x => x.Weight * x.Neuron.Value);
}