public void Setup()
{
Pattern1 = new HopfieldPattern(0.0, 1.0, 0.0, 1.0);
Pattern2 = new HopfieldPattern(1.0, 0.0, 0.0, 1.0);
Network = new HopfieldNetwork(4);
Network.Train(Pattern1);
Network.Train(Pattern2);
}
/**
* A simple main method to test the Hopfield neural network.
*
* @param args
* Not used.
*/
static void Main(string[] args)
{
// Create the neural network.
HopfieldNetwork network = new HopfieldNetwork(4);
// This pattern will be trained
bool[] TrainingPattern = { true, true, false, false };
// This pattern will be presented
bool[] PresentedPattern = { true, false, false, false };
bool[] result;
// train the neural network with pattern1
Console.WriteLine("Training Hopfield network with: "
+ FormatBoolean(TrainingPattern));
network.Train(TrainingPattern);
// present pattern1 and see it recognized
result = network.Present(TrainingPattern);
Console.WriteLine("Presenting pattern:" + FormatBoolean(TrainingPattern)
+ ", and got " + FormatBoolean(result));
// Present pattern2, which is similar to pattern 1. Pattern 1
// should be recalled.
result = network.Present(PresentedPattern);
Console.WriteLine("Presenting pattern:" + FormatBoolean(PresentedPattern)
+ ", and got " + FormatBoolean(result));
Console.ReadLine();
}
public void GetResult()
{
var network = new HopfieldNetwork();
network.Train(new Dictionary <string, string>
{
{ "1", Pattern1 },
{ "2", Pattern2 }
});
var result = network.GetResult(Pattern1);
Assert.AreEqual(Pattern1, result);
}
public void TrainEventTest()
{
var network = new HopfieldNetwork();
network.OnItemProcessed += (sender, args) =>
{
Assert.AreEqual(Math.Sqrt(network.NumberOfNeurons), args.ItemsCount);
};
network.Train(new Dictionary <string, string>
{
{ "1", Pattern1 },
{ "2", Pattern2 }
});
}
public void EvaluateEnergyFunctionTest()
{
var network = new HopfieldNetwork();
network.Train(new Dictionary <string, string>
{
{ "1", Pattern1 },
{ "2", Pattern2 }
});
var energyState = network.CurrentEnergyState;
network.GetResult(Pattern3);
Assert.IsTrue(network.CurrentEnergyState <= energyState);
}
private void TrainButton_Click(object sender, RoutedEventArgs e)
{
var colCount = 5;
var rowCount = 5;
var pattern = new double[colCount * rowCount];
for (var row = 0; row < rowCount; row++)
{
for (var col = 0; col < colCount; col++)
{
pattern[row * colCount + col] = ((ToggleButton)_GetControlIn(DrawingGrid, new GridCoordinates(row, col))).IsChecked.Value
? 1.0
: 0.0;
}
}
var hopfieldPattern = new HopfieldPattern(pattern);
hopfieldNetwork = hopfieldNetwork ?? new HopfieldNetwork(25);
hopfieldNetwork.Train(hopfieldPattern);
}
