/// <summary>
/// Force any neurons that did not win to off-load patterns from overworked
/// neurons.
/// </summary>
///
/// <param name="won"></param>
/// <param name="leastRepresented"></param>
/// <param name="matrix">The synapse to modify.</param>
/// <returns>True if a winner was forced.</returns>
private bool ForceWinners(Matrix matrix, int[] won,
IMLData leastRepresented)
{
double maxActivation = Double.MinValue;
int maxActivationNeuron = -1;
IMLData output = _network.Compute(leastRepresented);
// Loop over all of the output neurons. Consider any neurons that were
// not the BMU (winner) for any pattern. Track which of these
// non-winning neurons had the highest activation.
for (int outputNeuron = 0; outputNeuron < won.Length; outputNeuron++)
{
// Only consider neurons that did not "win".
if (won[outputNeuron] == 0)
{
if ((maxActivationNeuron == -1) ||
(output[outputNeuron] > maxActivation))
{
maxActivation = output[outputNeuron];
maxActivationNeuron = outputNeuron;
}
}
}
// If a neurons was found that did not activate for any patterns, then
// force it to "win" the least represented pattern.
if (maxActivationNeuron != -1)
{
CopyInputPattern(matrix, maxActivationNeuron, leastRepresented);
return(true);
}
return(false);
}
