internal static float[] GetDeltasHiddenLayer(float[] outputSignals, float[][] weightsNextLayer, float[] deltasErrorsNextLayer, ActivationFunc activationFunc)
{
int _neuronsCountThisLayer = outputSignals.Length;
int _neuronsCountNextLayer = deltasErrorsNextLayer.Length;
float[] _deltasErrors = new float[outputSignals.Length];
float _sumWeightsAndDeltasNextLayer;
float _derivativeActivFunc;
for (int _neuron = 0; _neuron < _neuronsCountThisLayer; _neuron++)
{
_sumWeightsAndDeltasNextLayer = GetSumWeightsAndDeltasNextLayer(_neuron);
_derivativeActivFunc = NeuralMath.GetDerivativeByFunction(outputSignals[_neuron], activationFunc);
_deltasErrors[_neuron] = _sumWeightsAndDeltasNextLayer * _derivativeActivFunc;
}
return(_deltasErrors);
float GetSumWeightsAndDeltasNextLayer(int neuronPrevLayer)
{
float _sumWeightsAndDeltas = 0;
for (int _neuronNextLayer = 0; _neuronNextLayer < _neuronsCountNextLayer; _neuronNextLayer++)
{
_sumWeightsAndDeltas += deltasErrorsNextLayer[_neuronNextLayer] * weightsNextLayer[neuronPrevLayer][_neuronNextLayer];
}
return(_sumWeightsAndDeltas);
}
}
internal static float[] GetDeltasOutputLayer(float[] outputSignals, float[] expectedSignals, ActivationFunc activationFunc)
{
int _neuronsCountThisLayer = outputSignals.Length;
float[] _deltasErrors = new float[_neuronsCountThisLayer];
float _errorOutSignal;
float _derivativeActivFunc;
for (int _neuron = 0; _neuron < _neuronsCountThisLayer; _neuron++)
{
_errorOutSignal = expectedSignals[_neuron] - outputSignals[_neuron];
_derivativeActivFunc = NeuralMath.GetDerivativeByFunction(outputSignals[_neuron], activationFunc);
_deltasErrors[_neuron] = _errorOutSignal * _derivativeActivFunc;
}
return(_deltasErrors);
}
