internal LearningConnection(INeuralConnection connection, ILearningRule rule)
{
Contract.Requires(connection != null);
Contract.Requires(rule != null);
Connection = connection;
Rule = rule;
}
internal void AddConnection(INeuralConnection connection, ILearningRule rule)
{
Contract.Requires(connection != null);
Contract.Requires(rule != null);
Contract.Requires(rule.AlgorithmType == GetType());
connectionList.AddLast(new LearningConnection(connection, rule));
}
private static void Update(INeuralConnection conn, WeightDecayRule rule)
{
double w4 = Math.Pow(conn.Weight, 4.0);
double div = w4 + rule.Cutoff4;
if (div != 0.0)
{
double delta = (w4 / div) * rule.Factor * conn.Weight;
conn.Weight += delta;
}
}
internal QuantumWeight(INeuralConnection connection)
{
Contract.Requires(connection != null);
this.connection = connection;
}
/// <summary>
/// Applies an algorithm that utilizes this Trait's Intensity to the Neural Connection
/// </summary>
public INeuralConnection AdjustNeuralConnection(INeuralConnection connection)
{
return connection;
}
/// <summary>
/// Adds an outbound connection to another node (either another network or a neuron) in the outer network.
/// </summary>
/// <param name="outboundConnection">The outbound connection to add.</param>
public void AddOutboundConnection(INeuralConnection outboundConnection)
{
const string MethodName = "AddOutboundConnection";
Logger.TraceIn(this.name, MethodName);
if (outboundConnection == null)
{
throw new ArgumentNullException("outboundConnection");
}
if (!this.outboundConnections.Contains(outboundConnection))
{
this.outboundConnections.Add(outboundConnection);
}
Logger.TraceOut(this.name, MethodName);
}
public void RemoveNeuralOutput(INeuralConnection conn)
{
if (conn.Source == this)
conn.Destination = null;
inputConnections.Remove(conn);
}
public void AddNeuralOutput(INeuralConnection conn)
{
if (conn.Source != this)
conn.Source = this;
outputConnections.Add(conn);
}