Encog.Neural.Thermal.HopfieldNetwork.AddPattern C# (CSharp) Method

        public void AddPattern(IMLData pattern)
        {
            if (pattern.Count != NeuronCount)
            {
                throw new NeuralNetworkError("Network with " + NeuronCount
                                             + " neurons, cannot learn a pattern of size "
                                             + pattern.Count);
            }

            // Create a row matrix from the input, convert boolean to bipolar
            Matrix m2 = Matrix.CreateRowMatrix(pattern.Data);
            // Transpose the matrix and multiply by the original input matrix
            Matrix m1 = MatrixMath.Transpose(m2);
            Matrix m3 = MatrixMath.Multiply(m1, m2);

            // matrix 3 should be square by now, so create an identity
            // matrix of the same size.
            Matrix identity = MatrixMath.Identity(m3.Rows);

            // subtract the identity matrix
            Matrix m4 = MatrixMath.Subtract(m3, identity);

            // now add the calculated matrix, for this pattern, to the
            // existing weight matrix.
            ConvertHopfieldMatrix(m4);
        }

        public void Execute(IExampleInterface app)
        {
            this.app = app;

            // Create the neural network.
            BasicLayer hopfield;
            var network = new HopfieldNetwork(4);

            // This pattern will be trained
            bool[] pattern1 = {true, true, false, false};
            // This pattern will be presented
            bool[] pattern2 = {true, false, false, false};
            IMLData result;

            var data1 = new BiPolarMLData(pattern1);
            var data2 = new BiPolarMLData(pattern2);
            var set = new BasicMLDataSet();
            set.Add(data1);

            // train the neural network with pattern1
            app.WriteLine("Training Hopfield network with: "
                          + FormatBoolean(data1));

            network.AddPattern(data1);
            // present pattern1 and see it recognized
            result = network.Compute(data1);
            app.WriteLine("Presenting pattern:" + FormatBoolean(data1)
                          + ", and got " + FormatBoolean(result));
            // Present pattern2, which is similar to pattern 1. Pattern 1
            // should be recalled.
            result = network.Compute(data2);
            app.WriteLine("Presenting pattern:" + FormatBoolean(data2)
                          + ", and got " + FormatBoolean(result));
        }