AForge.Neuro.Learning.DeltaRuleLearning.Run C# (CSharp) Method

        public double Run( double[] input, double[] output )
        {
            // compute output of network
            double[] networkOutput = network.Compute( input );

            // get the only layer of the network
            Layer layer = network.Layers[0];
            // get activation function of the layer
            IActivationFunction activationFunction = ( layer.Neurons[0] as ActivationNeuron ).ActivationFunction;

            // summary network absolute error
            double error = 0.0;

            // update weights of each neuron
            for ( int j = 0; j < layer.Neurons.Length; j++ )
            {
                // get neuron of the layer
                ActivationNeuron neuron = layer.Neurons[j] as ActivationNeuron;
                // calculate neuron's error
                double e = output[j] - networkOutput[j];
                // get activation function's derivative
                double functionDerivative = activationFunction.Derivative2( networkOutput[j] );

                // update weights
                for ( int i = 0; i < neuron.Weights.Length; i++ )
                {
                    neuron.Weights[i] += learningRate * e * functionDerivative * input[i];
                }

                // update threshold value
                neuron.Threshold += learningRate * e * functionDerivative;

                // sum error
                error += ( e * e );
            }

            return error / 2;
        }