public void TestForwardSignal()
{
var rand = new Random(123456);
var NLA = new NeuralLayer(1);
var NLB = new NeuralLayer(1);
NLA.SignalReceive = NLB.SignalReceive;
NLA.Bias[0] = (float)rand.NextDouble();
for (int iteration = 0; iteration < 10; iteration++)
{
NLA.SignalReceive[0] = (float)rand.NextDouble();
NLA.ForwardSignal();
NLB.ForwardSignal();
NLB.ErrorReceive[0] = NLA.SignalRespond[0] - NLB.SignalRespond[0];
NLB.FeedBackError();
NLB.UpdateWeight(0.5f, 0.25f);
}
Assert.Equal(NLB.Bias[0], NLA.Bias[0], 3);
}
public void TestAll()
{
int InputCount = 2;
int HiddenCount = 10;
int OutputCount = 1;
NeuralLayer InputLayer = new NeuralLayer(InputCount);
NeuralLayer HiddenLayer = new NeuralLayer(HiddenCount);
NeuralLayer OutputLayer = new NeuralLayer(OutputCount);
SynapticLayer SynLayerIH = new SynapticLayer(InputCount, HiddenCount);
SynapticLayer SynLayerHO = new SynapticLayer(HiddenCount, OutputCount);
SynLayerIH.SignalReceive = InputLayer.SignalRespond;
SynLayerIH.SignalRespond = HiddenLayer.SignalReceive;
SynLayerHO.SignalReceive = HiddenLayer.SignalRespond;
SynLayerHO.SignalRespond = OutputLayer.SignalReceive;
SynLayerHO.ErrorReceive = OutputLayer.ErrorRespond;
SynLayerHO.ErrorRespond = HiddenLayer.ErrorReceive;
SynLayerIH.ErrorReceive = HiddenLayer.ErrorRespond;
SynLayerIH.ErrorRespond = InputLayer.ErrorReceive;
var rand = new Random(123456);
for (int i = 0; i < InputCount; i++)
{
for (int j = 0; j < HiddenCount; j++)
{
SynLayerIH.Weights[j, i] = (float)rand.NextDouble();
}
}
for (int i = 0; i < HiddenCount; i++)
{
for (int j = 0; j < OutputCount; j++)
{
SynLayerHO.Weights[j, i] = (float)rand.NextDouble();
}
}
float O0 = 0;
for (int i = 0; i < 10; i++)
{
for (float I0 = -1; I0 < 1.1f; I0 += 2.0f)
{
for (float I1 = -1; I1 < 1.1f; I1 += 2.0f)
{
O0 = I1 < I0 ? 1 : (I1 > I0 ? 1 : -1);
//InputLayer.ForwardSignal();
InputLayer.SignalRespond[0] = I0;
InputLayer.SignalRespond[1] = I1;
SynLayerIH.ForwardSignal();
HiddenLayer.ForwardSignal();
SynLayerHO.ForwardSignal();
OutputLayer.ForwardSignal();
OutputLayer.ErrorRespond[0] = OutputLayer.SignalRespond[0] - O0;
OutputLayer.FeedBackError();
SynLayerHO.FeedBackError();
HiddenLayer.FeedBackError();
SynLayerIH.FeedBackError();
InputLayer.FeedBackError();
InputLayer.UpdateWeight(0.1f, 0.1f);
SynLayerIH.UpdateWeight(0.1f, 0.1f);
HiddenLayer.UpdateWeight(0.1f, 0.1f);
SynLayerHO.UpdateWeight(0.1f, 0.1f);
OutputLayer.UpdateWeight(0.1f, 0.1f);
}
}
}
}