public void GetGradientsForWeights()
{
//Arrange
float[] inputSignal = new float[]
{
0.95F, 0.55F, 0.90F
};
float[] deltasErrorThisLayer = new float[]
{
0.77F
};
float[][] expected = new float[][]
{
new float[] { 0.73149997F },
new float[] { 0.4235F },
new float[] { 0.692999959F }
};
//Act
var actual = Backpropagation.GetGradientsForWeights(inputSignal, deltasErrorThisLayer);
//Assert
for (int i = 0; i < expected.Length; i++)
{
for (int j = 0; j < expected[i].Length; j++)
{
Assert.AreEqual(expected[i][j], actual[i][j]);
}
}
}
protected virtual void UpdateWeightsForNeurons(LayerEventArgs layerEventArgs)
{
_GradientsForWeights = Backpropagation.GetGradientsForWeights(
_InputSignals[(int)layerEventArgs.NumberOfActiveDataset],
_DeltasErrorsOfNeurons);
_UpdatesForWeights = Backpropagation.GetUpdatesForWeights(
_GradientsForWeights,
_UpdatesForWeights,
layerEventArgs.LearningRate,
layerEventArgs.MomentumRate,
layerEventArgs.LearningOptimizing);
for (int synapse = 0; synapse < _SynapsesCount; synapse++)
{
for (int neuron = 0; neuron < _NeuronsCount; neuron++)
{
_NeuronWeights[synapse][neuron] += _UpdatesForWeights[synapse][neuron];
}
}
}