public INeuronLayersNeuronOutputs CalculateAllLayersOutputs(INeuronInputs passedInputs)
{
IList <INeuronOutputs> neuronLayerNeuronOutputs = new List <INeuronOutputs>(this._Values.Count);
INeuronInputs layerInputs = passedInputs;
foreach (INeuronLayer neuronLayer in this._Values)
{
INeuronOutputs neuronLayerOutput = neuronLayer.CalculateLayerOutput(layerInputs);
}
}
/// <summary>
/// Calculates the Outputs for all Neurons in the Layer given the Input.
/// Notes:
/// -float[Neuron Output]
/// </summary>
/// <param name="passedInput">The Input for all Neurons in the Layer.</param>
/// <returns>The Outputs of all Neurons in the Layer.</returns>
public INeuronOutputs CalculateLayerOutput(INeuronInputs passedInput)
{
IList <INeuronOutput> outputs = new List <INeuronOutput>((int)this.NumberOfNeurons);
for (int i = 0; i < this._Neurons.Count; i++)
{
INeuron neuron = this._Neurons[i];
INeuronOutput neuronOutput = neuron.CalculateOutput(passedInput);
outputs.Add(neuronOutput);
}
INeuronOutputs result = new NeuronOutputs(outputs);
return(result);
}
/// <summary>
/// Calculates Output for the Network.
/// Notes:
/// -float[Neuron Output].
/// </summary>
/// <param name="passedInput">The Input for the Network.</param>
/// <returns>The Output of the Output Layer.</returns>
public INeuronOutputs CalculateNetworkOutput(INeuronInputs passedInput)
{
INeuronInputs nextLayerInput = passedInput;
IEnumerator <INeuronLayer> neuronLayersEnumeartor = this._AllNeuronLayers.Values;
INeuronOutputs result;
while (neuronLayersEnumeartor.MoveNext())
{
INeuronLayer currentNeuronLayer = neuronLayersEnumeartor.Current;
result = currentNeuronLayer.CalculateLayerOutput(nextLayerInput);
nextLayerInput = result;
}
return(result);
}
/// <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);
}
public INeuronsNeuronOutput CalculateNeuronsOutput(INeuronInputs passedNeuronInputs)
{
throw new NotImplementedException();
}
