private void updateNodeWeights(SLPNode outputNode, bool[] input, double nodeError)
{
double LEARNING_RATE = 0.1;
for (int i = 0; i < input.Length - 1; i++)
{
if (input[i])
{
outputNode.weights[inputNodes[i]] += LEARNING_RATE * nodeError;
}
}
}
internal double calcNodeOutput(SLPNode node, bool[] input)
{
double result = 0;
for (int i = 0; i < input.Length - 1; i++)
{
if (input[i])
{
result += 1 * node.weights[inputNodes[i]];
}
}
return(result /= 16 * 16);
}
public SingleLayerPerceptron(int inputs, int outputs)
{
for (int i = 0; i < inputs; i++)
{
inputNodes.Add(new SLPNode());
}
for (int i = 0; i < outputs; i++)
{
SLPNode outputNode = new SLPNode();
Random random = new Random();
foreach (SLPNode inputNode in inputNodes)
{
outputNode.weights.Add(inputNode, random.Next(-1000, 1000) * 0.001);
}
outputNodes.Add(outputNode);
}
}
