using System;

using Accord.Neuro;

using Accord.Neuro.Learning;

​

​

public class Program

{

​

    public static void Main()

    {

    double[][] input = new double[4][] {

    new double[] {0, 0}, new double[] {0, 1},

    new double[] {1, 0}, new double[] {1, 1}

};

double[][] output = new double[4][] {

    new double[] {0}, new double[] {1},

    new double[] {1}, new double[] {0}

};

// create neural network

ActivationNetwork   network = new ActivationNetwork(

    new SigmoidFunction( 2 ),

    2, // two inputs in the network

    2, // two neurons in the first layer

    1 ); // one neuron in the second layer

// create teacher

BackPropagationLearning teacher = new BackPropagationLearning( network );

// loop

        double asoLoo=1;

while (asoLoo>.05)

{

    // run epoch of learning procedure

    double error = teacher.RunEpoch( input, output );

    // ...    // check error value to see if we need to stop

   asoLoo=error;

​

}

                Console.Write(asoLoo);

​

    }

}