public virtual void RecieveSignal(double value, Network.ActivateFunction activFunc)
{
Interlocked.Exchange(ref Value, Value + value);
Interlocked.Decrement(ref AdmissionsLeft);
if (AdmissionsLeft == 0)
{
SendSignal(activFunc);
}
}
public override void RecieveSignal(double value, Network.ActivateFunction activFunc)
{
Interlocked.Exchange(ref Value, Value + value);
Interlocked.Decrement(ref AdmissionsLeft);
if (AdmissionsLeft == 0)
{
Value = activFunc(Value);
}
}
public override void SendSignal(Network.ActivateFunction activFunc)
{
Parallel.ForEach(NextNeurons, nextNeuron =>
{
nextNeuron.Key.RecieveSignal(nextNeuron.Value * Value, activFunc);
if (WriteLog)
{
Outputter.Log($"Сигнал {NeuronName} - {nextNeuron.Key.NeuronName} отправлен = {nextNeuron.Value * Value}");
}
});
}
public virtual void SendSignal(Network.ActivateFunction activFunc)
{
Parallel.ForEach(NextNeurons, nextNeuron =>
{
double res = activFunc(Value);
nextNeuron.Key.RecieveSignal(res * nextNeuron.Value, activFunc);
if (WriteLog)
{
Outputter.Log($"Сигнал {NeuronName} - {nextNeuron.Key.NeuronName} отправлен = {Value} * {nextNeuron.Value} -> {res} * {nextNeuron.Value}");
}
Value = res;
}
);
}
static void Main(string[] args)
{
MyActivateFunc = delegate(double value)
{
return(value >= 0 ? 1 : 0);
};
try
{
Network network = new Network(new Network.Functions(MyActivateFunc, null, null), 1, 1, 2, 4, 1, 1);
network[0, 0].AddNextNeuron(network[1, 1], -1);
network[0, 0].AddNextNeuron(network[1, 2], -1);
network[0, 1].AddNextNeuron(network[1, 1], -1);
network[0, 1].AddNextNeuron(network[1, 2], -1);
network[1, 0].AddNextNeuron(network[1, 1], 1.5);
network[1, 0].AsOffset();
network[1, 3].AddNextNeuron(network[1, 2], 0.5);
network[1, 3].AsOffset();
network[1, 1].AddNextNeuron(network[3, 0], 1);
network[1, 2].AddNextNeuron(network[3, 0], -1);
network[2, 0].AddNextNeuron(network[3, 0], -0.5);
network[2, 0].AsOffset();
Outputter.Log(network.ToString());
foreach (double res in network.GetResult(0, 0))
{
/* Выведет -0.5 => 0*/
Outputter.Log("Ответ: " + res);
}
}
catch (Exception ex)
{
Outputter.Error(ex.Message);
}
Console.ReadLine();
}
static void Main(string[] args)
{
MyActivateFunc = delegate(double value)
{
return(1 / (1 + Math.Exp(-value)));
};
try
{
NetworkREP network = new NetworkREP(new Network.Functions(MyActivateFunc, null, null), 2, 4, 1, 1);
network.LearningNorm = 0.25;
network.InertialTerm = 1;
network[0, 0].AddNextNeuron(network[1, 1], -0.2);
network[0, 0].AddNextNeuron(network[1, 2], -0.1);
network[0, 1].AddNextNeuron(network[1, 1], 0.1);
network[0, 1].AddNextNeuron(network[1, 2], 0.3);
network[1, 0].AddNextNeuron(network[1, 1], 0.1);
network[1, 0].AsOffset();
network[1, 3].AddNextNeuron(network[1, 2], 0.1);
network[1, 3].AsOffset();
network[1, 1].AddNextNeuron(network[3, 0], 0.2);
network[1, 2].AddNextNeuron(network[3, 0], 0.3);
network[2, 0].AddNextNeuron(network[3, 0], 0.2);
network[2, 0].AsOffset();
foreach (double res in network.GetResult(1, 0))
{
Outputter.Log("Ответ: " + res);
}
Console.ReadLine();
Console.WriteLine();
for (int i = 0; i < 10000; i++)
{
network.Learning(new double[] { 0, 1 }, new double[] { 0 });
network.Learning(new double[] { 0, 0 }, new double[] { 0 });
network.Learning(new double[] { 1, 0 }, new double[] { 0 });
network.Learning(new double[] { 1, 1 }, new double[] { 1 });
}
Console.WriteLine("Done.");
Console.ReadLine();
foreach (double res in network.GetResult(1, 0))
{
Outputter.Log("Ответ: " + res);
}
Console.ReadLine();
foreach (double res in network.GetResult(0, 1))
{
Outputter.Log("Ответ: " + res);
}
Console.ReadLine();
foreach (double res in network.GetResult(0, 0))
{
Outputter.Log("Ответ: " + res);
}
Console.ReadLine();
foreach (double res in network.GetResult(1, 1))
{
Outputter.Log("Ответ: " + res);
}
}
catch (Exception ex)
{
Outputter.Error(ex.Message);
}
Console.ReadLine();
}
