static void ForwardMLP()
{
MultiLayerPerceptronNetwork network = new MultiLayerPerceptronNetwork( new double[] { -1, -1 }, 2, 1, 0.5 );
network.Forward();
Console.WriteLine("MLP output: ");
foreach (double output in network.GetOutputs())
Console.Write("{0}\t", output);
}
static void BackwardMLP()
{
MultiLayerPerceptronNetwork network = new MultiLayerPerceptronNetwork(2, 1, 0.5);
Console.WriteLine("Training network...");
for (int i = 0; i < 100; i++)
{
network.Backward(new double[] { -1.0, -1.0 }, new double[]{ -1.0 });
Console.WriteLine("{0}: -1.0, -1.0 = {1:f6}", i, network.GetOutputs()[0]);
network.Backward(new double[] { -1.0, 1.0 }, new double[]{ 1.0 });
Console.WriteLine("{0}: -1.0, 1.0 = {1:f6}", i, network.GetOutputs()[0]);
network.Backward(new double[] { 1.0, -1.0 }, new double[]{ 1.0 });
Console.WriteLine("{0}: 1.0, -1.0 = {1:f6}", i, network.GetOutputs()[0]);
network.Backward(new double[] { 1.0, 1.0 }, new double[]{ -1.0 });
Console.WriteLine("{0}: 1.0, 1.0 = {1:f6}", i, network.GetOutputs()[0]);
Console.WriteLine();
}
}