/// <summary>
/// Add a pattern for training.
/// </summary>
/// <param name="pattern">The pattern to add.</param>
public void AddPattern(double[] pattern)
{
for (int i = 0; i < _sumMatrix.Length; i++)
{
for (int j = 0; j < _sumMatrix.Length; j++)
{
_sumMatrix[i][j] = 0;
}
}
double n = _network.InputCount;
for (int i = 0; i < _sumMatrix.Length; i++)
{
for (int j = 0; j < _sumMatrix.Length; j++)
{
double t1 = (pattern[i] * pattern[j]) / n;
double t2 = (pattern[i] * CalculateLocalField(j, pattern)) / n;
double t3 = (pattern[j] * CalculateLocalField(i, pattern)) / n;
double d = t1 - t2 - t3;
_sumMatrix[i][j] += d;
}
}
for (int i = 0; i < _sumMatrix.Length; i++)
{
for (int j = 0; j < _sumMatrix.Length; j++)
{
_network.SetWeight(i, j, _network.GetWeight(i, j) + _sumMatrix[i][j]);
}
}
}
/// <summary>
/// Add a pattern for training.
/// </summary>
/// <param name="pattern">The pattern to add.</param>
public void AddPattern(double[] pattern)
{
for (var i = 0; i < _sumMatrix.Length; i++)
{
for (var j = 0; j < _sumMatrix.Length; j++)
{
_sumMatrix[i][j] = 0;
}
}
double n = _network.InputCount;
for (var i = 0; i < _sumMatrix.Length; i++)
{
for (var j = 0; j < _sumMatrix.Length; j++)
{
var t1 = pattern[i] * pattern[j] / n;
var t2 = pattern[i] * CalculateLocalField(j, pattern) / n;
var t3 = pattern[j] * CalculateLocalField(i, pattern) / n;
var d = t1 - t2 - t3;
_sumMatrix[i][j] += d;
}
}
for (var i = 0; i < _sumMatrix.Length; i++)
{
for (var j = 0; j < _sumMatrix.Length; j++)
{
_network.SetWeight(i, j, _network.GetWeight(i, j) + _sumMatrix[i][j]);
}
}
}
/// <summary>
/// Learn the added patterns.
/// </summary>
public void Learn()
{
if (_patternCount == 0)
{
throw new AIFHError("Please add a pattern before learning. Nothing to learn.");
}
for (var i = 0; i < _sumMatrix.Length; i++)
{
for (var j = 0; j < _sumMatrix.Length; j++)
{
_network.SetWeight(i, j, _sumMatrix[i][j] / _patternCount);
}
}
}
