/// <summary>
/// Calculates the Output for a given Input using the Sigmoid Function.
/// </summary>
/// <param name="passedInput">The Input.</param>
/// <param name="passedThreshold">The Threshold.</param>
/// <returns>The Output for the Sigmoid Function.</returns>
public INeuronOutput CalculateOutput(INeuronActivationFunctionInput passedInput, INeuronThreshold passedThreshold)
{
float resultValue = (float)(1 / (1 + Math.Exp((-passedInput.Value) / passedThreshold.Value)));
INeuronOutput result = new NeuronOutput(resultValue);
return(result);
}
/// <summary>
/// Calculates the Output for a given Input using the Step Function.
/// </summary>
/// <param name="passedInput">The Input.</param>
/// <param name="passedThreshold">The Threshold.</param>
/// <returns>The Output for the Step Function.</returns>
public INeuronOutput CalculateOutput(INeuronActivationFunctionInput passedInput, INeuronThreshold passedThreshold)
{
float resultValue = (passedInput.Value >= passedThreshold.Value) ? 1 : 0;
INeuronOutput result = new NeuronOutput(resultValue);
return(result);
}
// Prints formatted neuron values to console.
public void ShowNeuron()
{
Console.Write("Weights: ");
foreach (var weight in NeuronWeights)
{
Console.Write(weight + " ");
}
Console.Write("Output: " + NeuronOutput.ToString());
Console.Write(" Delta: " + NeuronDelta.ToString());
Console.WriteLine();
}
private void AddLayerOutput(int neurons)
{
var layer = new LayerOutput
{
Neurons = new List <Neuron>(),
};
for (var i = 1; i <= neurons; i++)
{
var neuron = new NeuronOutput
{
Connections1 = new List <Connection>(),
Connections2 = new List <Connection>(),
};
neuron.Bias = Math2.Range(-1f, 1);
layer.Neurons.Add(neuron);
}
this.Layers.Add(layer);
}
/// <summary>
/// Calculates the Output for the Neuron given the Input.
/// </summary>
/// <param name="passedInput">The Input for the Neuron.</param>
/// <returns>The Output of the Neuron.</returns>
public INeuronOutput CalculateOutput(INeuronInputs passedInputs)
{
float total = 0.0f;
IEnumerator <INeuronWeight> neuronWeightsEnumerator = this.Weights.Weights;
IEnumerator <INeuronInput> neuronInputsEnumerator = passedInputs.Values;
while (neuronWeightsEnumerator.MoveNext() && neuronInputsEnumerator.MoveNext())
{
INeuronWeight currentWeight = neuronWeightsEnumerator.Current;
INeuronInput currentInput = neuronInputsEnumerator.Current;
float tempValue = currentWeight.Value * currentInput.Value;
total += tempValue;
}
float computedResult = this.ActivationFunction.CalculateOutput(total, this.Threshold);
INeuronOutput result = new NeuronOutput(computedResult);
return(result);
}
