public override void Learning(double[] args, double[] expectedRes)
{
if ((args.Length != NeuronsNetwork[0].Length) ||
expectedRes.Length != NeuronsNetwork[NeuronsNetwork.Length - 1].Length)
{
throw new ArgumentException("Количество входных данных не соответсвует размеру (выходного слоя + ожидаемых результатов)");
}
GetResult(args);
if (WriteLog)
{
Outputter.Log("Обучение...");
}
Task.Run(() =>
{
Parallel.ForEach(NeuronsNetwork[NeuronsNetwork.Length - 1], outputNeuron =>
{
outputNeuron.RecieveErrorSigmoid(null, LearningNorm, InertialTerm,
expectedRes[(outputNeuron as OutputNeuron).NeuronId]);
}
);
}
).Wait();
if (WriteLog)
{
Outputter.Log("Обучение завершено.");
}
}
public virtual void RecieveErrorSigmoid(Neuron errorNeuron,
double learningNorm, double inertialTerm, double?expectedValue = null)
{
Interlocked.Exchange(ref ErrorSummary, ErrorSummary + errorNeuron.ErrorSummary);
Interlocked.Decrement(ref ErrorsLeft);
if (ErrorsLeft == 0)
{
ErrorSummary = Value * (1 - Value) * ErrorSummary * NextNeurons[errorNeuron];
if (WriteLog)
{
Outputter.Log($"Вес {NeuronName} - {errorNeuron.NeuronName} изменён {NextNeurons[errorNeuron]} - ");
}
errorNeuron.LastNeurons[this] = NextNeurons[errorNeuron] = NextNeurons[errorNeuron] * inertialTerm
+ learningNorm * Value * errorNeuron.ErrorSummary;
if (WriteLog)
{
Outputter.Log($"{NextNeurons[errorNeuron]}");
}
if (LastNeurons.Count != 0)
{
for (int i = 0; i < LastNeurons.Keys.Count; i++)
{
LastNeurons.Keys.ElementAt(i).RecieveErrorSigmoid(this, learningNorm, inertialTerm);
}
}
}
}
public override void SendSignal(Network.ActivateFunction activFunc)
{
Parallel.ForEach(NextNeurons, nextNeuron =>
{
nextNeuron.Key.RecieveSignal(nextNeuron.Value * Value, activFunc);
if (WriteLog)
{
Outputter.Log($"Сигнал {NeuronName} - {nextNeuron.Key.NeuronName} отправлен = {nextNeuron.Value * Value}");
}
});
}
public double[] GetResult(params double[] args)
{
ClearNeurons();
if (args.Length != NeuronsNetwork[0].Length)
{
throw new ArgumentException("Количество входных данных не соответсвует размеру входного слоя.");
}
if (WriteLog)
{
Outputter.Log($"Входные данные: ");
}
for (int i = 0; i < args.Length; i++)
{
if (WriteLog)
{
Outputter.Log($"{NeuronsNetwork[0][i].NeuronName} = {args[i]}");
}
}
Task.Run(() =>
{
Parallel.ForEach(NeuronsNetwork[0], inputNeuron =>
{
inputNeuron.RecieveSignal(args[(inputNeuron as InputNeuron).NeuronId], NetFunctions.ActivateFunc);
}
);
}
).Wait();
Task.Run(() =>
{
for (int i = 1; i < NeuronsNetwork.Length - 1; i++)
{
Parallel.ForEach(NeuronsNetwork[i].Where(t => t.GetRemainingSignals() == 0), hiddenNeuron =>
{
hiddenNeuron.SendSignal(NetFunctions.ActivateFunc);
}
);
}
}
).Wait();
double[] result = new double[NeuronsNetwork[NeuronsNetwork.Length - 1].Length];
for (int i = 0; i < result.Length; i++)
{
result[i] = NeuronsNetwork[NeuronsNetwork.Length - 1][i].GetValue();
}
return(result);
}
public virtual void AddLastNeuron(Neuron neuron, double weight)
{
if (LastNeurons.ContainsKey(neuron))
{
if (WriteLog)
{
Outputter.Warning($"Нейроны {NeuronName} и {neuron.NeuronName} уже обьединены обратной связью.");
}
}
else
{
LastNeurons.Add(neuron, weight);
}
}
public virtual void SendSignal(Network.ActivateFunction activFunc)
{
Parallel.ForEach(NextNeurons, nextNeuron =>
{
double res = activFunc(Value);
nextNeuron.Key.RecieveSignal(res * nextNeuron.Value, activFunc);
if (WriteLog)
{
Outputter.Log($"Сигнал {NeuronName} - {nextNeuron.Key.NeuronName} отправлен = {Value} * {nextNeuron.Value} -> {res} * {nextNeuron.Value}");
}
Value = res;
}
);
}
public virtual void AddNextNeuron(Neuron neuron, double?weight = null)
{
if (NextNeurons.ContainsKey(neuron))
{
if (WriteLog)
{
Outputter.Warning($"Нейроны {NeuronName} и {neuron.NeuronName} уже обьединены прямой связью.");
}
}
else
{
Random rand = new Random();
weight = weight == null?rand.NextDouble() : weight;
NextNeurons.Add(neuron, weight.Value);
neuron.AddLastNeuron(this, weight.Value);
neuron.AdmissionsLeft = ++neuron.MaxAdmissionsLeft;
}
}
public override void AsOffset()
{
IsOffset = true;
NeuronName += " (OFFSET)";
MaxAdmissionsLeft = AdmissionsLeft = 0;
Value = 1;
if (LastNeurons.Keys.Count != 0)
{
if (WriteLog)
{
Outputter.Warning($"При изменении свойства IsOffset нейрон {NeuronName} потерял связи с" +
$" {LastNeurons.Keys.Count} нейронами!");
}
}
while (LastNeurons.Keys.Count != 0)
{
LastNeurons.ElementAt(0).Key.RemoveNextNeuron(this);
LastNeurons.Remove(LastNeurons.ElementAt(0).Key);
}
}