/*
* Calcula distância euclidiana do padrão de entrada
*/
public double GetEuclideanDistance(DataSetObject pattern)
{
double dist = 0;
if (pattern.GetInputLenght() != weights.Length)
{
throw new Exception("Incorrect data format!");
}
else
{
double[] inputWeights = pattern.GetInput();
if (weights.Length != inputWeights.Length)
{
throw new Exception("Incorrect data format!");
}
else
{
for (int x = 0; x < weights.Length; x++)
{
dist += ((inputWeights[x] - weights[x]) * (inputWeights[x] - weights[x]));
}
}
}
return(dist);
}
/*
* Dado um padrão de entrada e uma variável de aprendizado, atualiza os pesos do neurônio
*/
public void UpdateWeights(DataSetObject pattern, double learningRate)
{
if (pattern.GetInputLenght() != weights.Length)
{
throw new Exception("Incorrect data format!");
}
else
{
double[] inputWeights = pattern.GetInput();
for (int i = 0; i < inputWeights.Length; i++)
{
weights[i] += learningRate * (inputWeights[i] - weights[i]);
}
}
}
