Simple neural network example written in java

Neural.java

import java.util.Random;

public class Neural {
	static double weights[][] = new double[3][1]; 
	static double output[][] = new double[4][1]; 
	public static void main(String args[]) {

		double input[][] =  {{ 0, 0, 1 }, {1, 1, 1}, { 1,0,1 }, {0,1,1}};

		double trueoutput[][] = { {0}, {1}, {1}, {0}};

		double testoutput[][] = {  {0, 1, 0}, {1,0,0} , { 0,0,0 }, {1,1,0}};

		GenWeights();
		for (int i=0; i < 1000; i++)
			train(input, trueoutput);

		application(testoutput);
		for(int i=0; i< output.length; i++) { 
			for(int j=0; j< output[i].length; j++) {
				System.out.print(output[i][j] + " ");	
			}
			System.out.println();
		}

	}

	static void application(double[][] input) {
		for(int i=0; i< output.length; i++) {
			for(int j=0; j< output[i].length; j++) {
				output[i][j] = sigmoid(dot(input, weights)[i][j]);
			}
		}
	}

	static void train(double[][] input, double trueoutput[][]) {

		double[][] error = new double[output.length][output[0].length];
		double[][] adjustment = new double[weights.length][weights[0].length];
		double[][] Errchange = new double[output.length][output[0].length];

		for(int i=0; i< output.length; i++) {
			for(int j=0; j< output[i].length; j++)
				output[i][j] = sigmoid(dot(input, weights)[i][j]);
		}


		for(int i=0; i< error.length; i++) {
			for(int j=0; j< error[i].length; j++)
				error[i][j] = trueoutput[i][j] - output[i][j];

		}

		for(int i=0; i< Errchange.length; i++) {
			for(int j=0; j< Errchange[i].length; j++) 
				Errchange[i][j] = error[i][j]*deriva_sigmoid(output[i][j]);
		}

		adjustment = dot(T(input), Errchange);

		for(int i=0; i< weights.length; i++) {
			for(int j=0; j< weights[i].length; j++) 
				weights[i][j] += adjustment[i][j];
		}
	}

	static void GenWeights() {
		Random rand = new Random(8);
		for (int i=0; i < weights.length; i++) {
			for(int j=0; j< weights[i].length; j++) {
				weights[i][j] = rand.nextDouble();
			}
		}
	}

	static double sigmoid(double d) {
		return 1 / (1 + Math.pow(Math.E,(-d)));
	}

	static double deriva_sigmoid(double x) {
		return x * (1 - x);
	}

	static double[][] T(double[][] a){
		double[][] c = new double[a[0].length][a.length];

		for (int i =0; i < a[0].length; i++)
			for (int j = 0; j < a.length; j++) {

				c[i][j] = a[j][i];

			}	

		return c;
	}

	static double[][] dot(double[][] arr, double[][] arr2){
		double[][] c = new double[arr.length][arr2[0].length];

		for (int x =0; x < arr.length; x ++)
			for (int i =0; i < arr2[0].length; i++) {
				for (int j =0; j < arr2.length; j++) {
					c[x][i] += arr[x][j]*arr2[j][i];
				}
			}

		return c;

	}


}

What's the program all about?

What's the program all about?
The output is the value of the first column