Test_Hopfield.java

package neuralnetworks;


public class Test_Hopfield {
    static float[] data [] = {
        {1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1},
        {-1, -1, -1, 1, -1, 1, -1, -1, -1, -1, -1, 1, -1},
        {-1, -1, -1, -1, -1, -1, -1, -11, 1, 1, -1, 1, -1},
        {1, -1, -1, -1, -1, -1, -1, -1, 1, -1, -1, -1, 1}
    };
    static Hopfield test;

    public static void main(String[] args) {
        test = new Hopfield(13);
        test.addTrainingData(data[0]);
        test.addTrainingData(data[1]);
        test.addTrainingData(data[2]);
        // if we add an extra example, then we overflow the capacity of this network:
        //test.addTrainingData(data[3]);
        test.train();
        helper(test, "pattern 0", data[0]);
        helper(test, "pattern 1", data[1]);
        helper(test, "pattern 2", data[2]);
        // if we add an extra example, then we overflow the capacity of this network:
        //helper(test, "pattern 3", data[3]);
    }

    private static void helper(Hopfield test, String s, float[] test_data) {
        float[] dd = new float[13];
        for (int i = 0; i < 13; i++) {
          dd[i] = test_data[i];
        }
        // change this to flip 1 or 2 bits:
        int NUM_BITS_TO_FLIP = 1;
        for (int i_scramble=0; i_scramble<NUM_BITS_TO_FLIP; i_scramble++) {
          int index = (int) (12.0f * (float) Math.random());
          dd[index] = -dd[index];
          //if (dd[index] < 0.0f)
          //  dd[index] = 1.0f;
          //else
          //  dd[index] = -1.0f;
        }
        float[] rr = test.recall(dd, 15);
        System.out.print(s+"\nOriginal data:      ");
        for (int i = 0; i < 13; i++) System.out.print(pp(test_data[i]) + " ");
        System.out.print("\nRandomized data:    ");
        for (int i = 0; i < 13; i++) System.out.print(pp(dd[i]) + " ");
        System.out.print("\nRecognized pattern: ");
        for (int i = 0; i < 13; i++) System.out.print(pp(rr[i]) + " ");
        System.out.println();
    }

    private static int pp(float x) {
        if (x > 0.1f) return 1;
        return 0;
    }
}