private void InitializeInputs(int numOfThisLayer)
{
if (numOfThisLayer == 0)
{
InitializeInputs_FirstLayerNeuron(); return;
}
Inputs = new NeuronInput[Layers[numOfThisLayer - 1].NeuronsList.Length];
}
private void AddLayerInput(int neurons)
{
var layer = new LayerInput
{
Neurons = new List <Neuron>(),
};
for (var i = 1; i <= neurons; i++)
{
var neuron = new NeuronInput
{
Connections1 = new List <Connection>(),
Connections2 = new List <Connection>(),
};
neuron.Bias = Math2.Range(-1f, 1);
layer.Neurons.Add(neuron);
}
this.Layers.Add(layer);
}
public void TestSigmoidalFunction()
{
NeuronInput inputA = new NeuronInput(0.67, 1.5);
NeuronInput inputB = new NeuronInput(0.5, 1.0);
NeuronInput inputC = new NeuronInput(0.8, 0.8);
NeuronInput[] inputs = new NeuronInput[3];
inputs[0] = inputA;
inputs[1] = inputB;
inputs[2] = inputC;
SigmoidNeuron neuron = new SigmoidNeuron(inputs, 3.0);
double output = neuron.SigmoidalFunction();
double expected = 0.99420529989699;
double delta = expected - output;
Assert.AreEqual(output, expected, delta);
}
private void InitializeInputs_FirstLayerNeuron()
{
Inputs = new NeuronInput[InputValues.Length];
}