Synapse.cs

public class Synapse : ISynapse
{
    internal INeuron _fromNeuron;
    internal INeuron _toNeuron;

    /// <summary>
    /// Weight of the connection.
    /// </summary>
    public double Weight { get; set; }

    /// <summary>
    /// Weight that connection had in previous itteration.
    /// Used in training process.
    /// </summary>
    public double PreviousWeight { get; set; }

    public Synapse(INeuron fromNeuraon, INeuron toNeuron, double weight)
    {
        _fromNeuron = fromNeuraon;
        _toNeuron = toNeuron;

        Weight = weight;
        PreviousWeight = 0;
    }

    public Synapse(INeuron fromNeuraon, INeuron toNeuron)
    {
        _fromNeuron = fromNeuraon;
        _toNeuron = toNeuron;

        var tmpRandom = new Random();
        Weight = tmpRandom.NextDouble();
        PreviousWeight = 0;
    }

    /// <summary>
    /// Get output value of the connection.
    /// </summary>
    /// <returns>
    /// Output value of the connection.
    /// </returns>
    public double GetOutput()
    {
        return _fromNeuron.CalculateOutput();
    }

    /// <summary>
    /// Checks if Neuron has a certain number as an input neuron.
    /// </summary>
    /// <param name="fromNeuronId">Neuron Id.</param>
    /// <returns>
    /// True - if the neuron is the input of the connection.
    /// False - if the neuron is not the input of the connection. 
    /// </returns>
    public bool IsFromNeuron(Guid fromNeuronId)
    {
        return _fromNeuron.Id.Equals(fromNeuronId);
    }

    /// <summary>
    /// Update weight.
    /// </summary>
    /// <param name="learningRate">Chossen learning rate.</param>
    /// <param name="delta">Calculated difference for which weight of the connection needs to be modified.</param>
    public void UpdateWeight(double learningRate, double delta)
    {
        PreviousWeight = Weight;
        Weight += learningRate * delta;
    }
}