/// <summary>
/// Feed Forward (FF) this NN with a given input Array
/// </summary>
/// <param name="inputs">NN Inputs</param>
/// <returns></returns>
public float[] FeedForward(float[] inputs)
{
// Add inputs to the Neuron Matrix
for (int i = 0; i < inputs.Length; i++)
{
neurons[0][i] = inputs[i];
}
// Itterate over all Neurons and compute FF values
for (int i = 1; i < layers.Length; i++)
{
for (int j = 0; j < layers[i]; j++)
{
// Init
float value = bias ? 1.0f : 0.0f;
for (int k = 0; k < neurons[i - 1].Length; k++)
{
// Sum off all Weights connections of this Neuron Weight values in their previous Layer
value += weights[i - 1][j][k] * neurons[i - 1][k];
}
// Hyperbolic Tangent activation
neurons[i][j] = NNMath.ActivateFunction(value);
}
}
// Return output Layer
return neurons[neurons.Length - 1];
}
/// <summary>
/// Generate Weight Matrix
/// </summary>
private void InitWeights()
{
// Weight Init (will be converted to 3D Array)
List<float[][]> weightsList = new List<float[][]>();
// Itterate over all Neurons that have a Weight connection
for (int i = 1; i < layers.Length; i++)
{
// Layer Weight List for this current Layer (will be converted to 2D Array)
List<float[]> layerWeightsList = new List<float[]>();
int neuronsInPreviousLayer = layers[i - 1];
// Itterate over all Neurons in this current Layer
for (int j = 0; j < layers[i]; j++)
{
// Neurons Weights
float[] neuronWeights = new float[neuronsInPreviousLayer];
// Itterate over all Neurons in the previous Layer and set the Weights randomly between 0.5f and -0.5
for (int k = 0; k < neuronsInPreviousLayer; k++)
{
// Give random Weights to Neuron Weights
neuronWeights[k] = NNMath.RandomWeightValue();
}
// Add Neuron Weights of this current Layer to Layer Weights
layerWeightsList.Add(neuronWeights);
}
// Add this Layers Weights converted into 2D Array into Weights List
weightsList.Add(layerWeightsList.ToArray());
}
// Convert to 3D Array
weights = weightsList.ToArray();
}