hopfield

import java.awt.*;
import javax.swing.*;
import java.awt.event.*;
/**
* Example: The Hopfield Neural Network
*
* This is an example that implements a Hopfield neural
* network. This example network contains four fully
* connected neurons. This file, Hopfield, implements a
* Swing interface into the other two neural network
* classes: Layer and Neuron.
*
* @author Jeff Heaton
* @version 1.0
*/
public class Hopfield extends JFrame implements ActionListener {
/**
* The number of neurons in this neural network.
*/
public static final int NETWORK_SIZE = 4;
/**
* The weight matrix for the four fully connected
* neurons.
*/
JTextField matrix[][] =
new JTextField[NETWORK_SIZE][NETWORK_SIZE];
/**
* The input pattern, used to either train
* or run the neural network. When the network
* is being trained, this is the training
* data. When the neural network is to be ran
* this is the input pattern.
*/
JComboBox input[] = new JComboBox[NETWORK_SIZE];
/**
* The output from each of the four neurons.
*/
JTextField output[] = new JTextField[NETWORK_SIZE];
/**
* The clear button. Used to clear the weight
* matrix.
*/
JButton btnClear = new JButton("Clear");
/**
* The train button. Used to train the
* neural network.
*/
JButton btnTrain = new JButton("Train");
/**
* The run button. Used to run the neural
* network.
*/
JButton btnRun = new JButton("Run");
/**
* Constructor, create all of the components and position
* the JFrame to the center of the screen.
*/
public Hopfield()
{
setTitle("Hopfield Neural Network");
// create connections panel
JPanel connections = new JPanel();
connections.setLayout(
new GridLayout(NETWORK_SIZE,NETWORK_SIZE) );
for ( int row=0;row < NETWORK_SIZE;row++ ) {
for ( int col=0;col < NETWORK_SIZE;col++ ) {
matrix[row][col] = new JTextField(3);
matrix[row][col].setText("0");
connections.add(matrix[row][col]);
}
}
Container content = getContentPane();
GridBagLayout gridbag = new GridBagLayout();
GridBagConstraints c = new GridBagConstraints();
content.setLayout(gridbag);
c.fill = GridBagConstraints.NONE;
c.weightx = 1.0;
// Weight matrix label
c.gridwidth = GridBagConstraints.REMAINDER; //end row
c.anchor = GridBagConstraints.NORTHWEST;
content.add(
new JLabel(
"Weight Matrix for the Hopfield Neural Network:"),c);
// Weight matrix
c.anchor = GridBagConstraints.CENTER;
c.gridwidth = GridBagConstraints.REMAINDER; //end row
content.add(connections,c);
c.gridwidth = 1;
// Input pattern label
c.anchor = GridBagConstraints.NORTHWEST;
c.gridwidth = GridBagConstraints.REMAINDER; //end row
content.add(
new JLabel(
"Click \"Train\" to train the following pattern:"),c);
// Input pattern
String options[] = { "0","1"};
JPanel inputPanel = new JPanel();
inputPanel.setLayout(new FlowLayout());
for ( int i=0;i < NETWORK_SIZE;i++ ) {
input[i] = new JComboBox(options);
inputPanel.add(input[i]);
}
c.gridwidth = GridBagConstraints.REMAINDER; //end row
c.anchor = GridBagConstraints.CENTER;
content.add(inputPanel,c);
// Output pattern label
c.anchor = GridBagConstraints.NORTHWEST;
c.gridwidth = GridBagConstraints.REMAINDER; //end row
content.add(
new JLabel("Click \"Run\" to see output pattern:"),c);
// Output pattern
JPanel outputPanel = new JPanel();
outputPanel.setLayout(new FlowLayout());
for ( int i=0; i < NETWORK_SIZE;i++ ) {
output[i] = new JTextField(3);
output[i].setEditable(false);
outputPanel.add(output[i]);
}
c.gridwidth = GridBagConstraints.REMAINDER; //end row
c.anchor = GridBagConstraints.CENTER;
content.add(outputPanel,c);
// Buttons
JPanel buttonPanel = new JPanel();
btnClear = new JButton("Clear");
btnTrain = new JButton("Train");
btnRun = new JButton("Run");
btnClear.addActionListener(this);
btnTrain.addActionListener(this);
btnRun.addActionListener(this);
buttonPanel.setLayout(new FlowLayout());
buttonPanel.add(btnClear);
buttonPanel.add(btnTrain);
buttonPanel.add(btnRun);
content.add(buttonPanel,c);
// adjust size and position
pack();
Toolkit toolkit = Toolkit.getDefaultToolkit();
Dimension d = toolkit.getScreenSize();
setLocation(
(int)(d.width-this.getSize().getWidth())/2,
(int)(d.height-this.getSize().getHeight())/2 );
setDefaultCloseOperation(WindowConstants.DISPOSE_ON_CLOSE);
setResizable(false);
}
/**
* Used to dispatch events from the buttons
* to the handler methods.
*
* @param e The event
*/
public void actionPerformed(ActionEvent e)
{
if ( e.getSource()==btnRun )
run();
else if ( e.getSource()==btnClear )
clear();
else if ( e.getSource()==btnTrain )
train();
}
/**
* Called when the neural network is to be ran against
* the input.
*/
protected void run()
{
boolean pattern[] = new boolean[NETWORK_SIZE];
int wt[][] = new int[NETWORK_SIZE][NETWORK_SIZE];
for ( int row=0; row < NETWORK_SIZE;row++ )
for ( int col=0; col < NETWORK_SIZE;col++ )
wt[row][col]=Integer.parseInt(matrix[row][col].getText());
for ( int row=0; row < NETWORK_SIZE;row++ ) {
int i = input[row].getSelectedIndex();
if ( i==0 )
pattern[row] = false;
else
pattern[row] = true;
}
Layer net = new Layer(wt);
net.activation(pattern);
for ( int row=0; row < NETWORK_SIZE;row++ ) {
if ( net.output[row] )
output[row].setText("1");
else
output[row].setText("0");
if ( net.output[row]==pattern[row] )
output[row].setBackground(java.awt.Color.green);
else
output[row].setBackground(java.awt.Color.red);
}
}
/**
* Called to clear the weight matrix.
*/
protected void clear()
{
for ( int row=0; row < NETWORK_SIZE;row++ )
for ( int col=0; col < NETWORK_SIZE;col++ )
matrix[row][col].setText("0");
}
/**
* Called to train the weight matrix based on the
* current input pattern.
*/
protected void train()
{
int work[][] = new int[NETWORK_SIZE][NETWORK_SIZE];
int bi[] = new int[NETWORK_SIZE];
for ( int x=0; x < NETWORK_SIZE;x++ ) {
if ( input[x].getSelectedIndex()==0 )
bi[x] = -1;
else
bi[x] = 1;
}
for ( int row=0; row < NETWORK_SIZE;row++ )
for ( int col=0; col < NETWORK_SIZE;col++ ) {
work[row][col] = bi[row]*bi[col];
}
for ( int x=0; x < NETWORK_SIZE;x++ )
work[x][x] =-1;
for ( int row=0; row < NETWORK_SIZE;row++ )
for ( int col=0; col < NETWORK_SIZE;col++ ) {
int i = Integer.parseInt(matrix[row][col].getText());
matrix[row][col].setText( "" + (i+work[row][col]));
}
}
/**
* Main program entry point, display the
* frame.
*
* @param args Command line arguments are not used
*/
static public void main(String args[])
{
JFrame f = new Hopfield();
f.show();
}
} < network_size;x++" col="0; col < NETWORK_SIZE;col++" i="0;
i < NETWORK_SIZE;i++" f="new" content="getContentPane();">