public void AdjustWeights(int inputIndex, double[] inputs)
{
for (var i = 0; i < _numNeurons; i++)
{
_hiddenWeights[i] -= (_outputData[inputIndex] - _expectedOutput[inputIndex]) * inputs[i] * _learnRate;
for (var j = 0; j < _numLearnNeurons; j++)
{
_inputWeights[j, i] -= (_outputData[inputIndex] - _expectedOutput[inputIndex]) *
Sigmoid.Derivative(inputs[i]) * _hiddenWeights[i] * _outputData[inputIndex] *
_learnRate;
}
}
}
public void Train(int inputIndex, double[] inputs)
{
for (var i = 0; i < _numNeurons; i++) //neuron
{
inputs[i] = 0.0;
for (var j = 0; j < _numLearnNeurons; j++) //weight
{
inputs[i] += _inputData[inputIndex] * _inputWeights[j, i];
}
inputs[i] = Sigmoid.Func(inputs[i]);
}
_outputData[inputIndex] = 0.0;
for (var i = 0; i < _numNeurons; i++)
{
_outputData[inputIndex] += _hiddenWeights[i] * inputs[i];
}
}