/// <summary>
/// Create a neural network for XOR.
/// </summary>
public static void ProcessXor()
{
Console.WriteLine("Boolean XOR");
var inputs = new List <InputNeuron>();
inputs.Add(new InputNeuron());
inputs.Add(new InputNeuron());
var hidden1 = new List <RegularNeuron>();
hidden1.Add(new RegularNeuron(-0.5));
hidden1.Add(new RegularNeuron(-1.5));
hidden1[0].Parents.Add(new Connection(1, inputs[0]));
hidden1[0].Parents.Add(new Connection(1, inputs[1]));
hidden1[1].Parents.Add(new Connection(1, inputs[0]));
hidden1[1].Parents.Add(new Connection(1, inputs[1]));
var hidden2 = new RegularNeuron(0.5);
hidden2.Parents.Add(new Connection(-1, hidden1[1]));
var output = new RegularNeuron(-1.5);
output.Parents.Add(new Connection(1, hidden1[0]));
output.Parents.Add(new Connection(1, hidden2));
TruthTable(inputs, output);
}
/// <summary>
/// Create a neural network for NOT.
/// </summary>
public static void ProcessNot()
{
Console.WriteLine("Boolean NOT");
List<InputNeuron> inputs = new List<InputNeuron>();
inputs.Add(new InputNeuron());
RegularNeuron output = new RegularNeuron(0.5);
output.Parents.Add(new Connection(-1, inputs[0]));
TruthTable(inputs, output);
}
/// <summary>
/// Create a neural network for NOT.
/// </summary>
public static void ProcessNot()
{
Console.WriteLine("Boolean NOT");
var inputs = new List <InputNeuron>();
inputs.Add(new InputNeuron());
var output = new RegularNeuron(0.5);
output.Parents.Add(new Connection(-1, inputs[0]));
TruthTable(inputs, output);
}
/// <summary>
/// Create a neural network for OR.
/// </summary>
public static void ProcessOr()
{
Console.WriteLine("Boolean OR");
List <InputNeuron> inputs = new List <InputNeuron>();
inputs.Add(new InputNeuron());
inputs.Add(new InputNeuron());
RegularNeuron output = new RegularNeuron(-0.5);
output.Parents.Add(new Connection(1, inputs[0]));
output.Parents.Add(new Connection(1, inputs[1]));
TruthTable(inputs, output);
}
/// <summary>
/// Display a truth table and query the neural network.
/// </summary>
/// <param name="inputs">The inputs.</param>
/// <param name="output">The output.</param>
public static void TruthTable(IList <InputNeuron> inputs, RegularNeuron output)
{
var v = new double[inputs.Count];
var done = false;
while (!done)
{
for (var i = 0; i < inputs.Count; i++)
{
inputs[i].Value = v[i];
}
var o = output.Compute();
Console.WriteLine(v + " : " + o);
// Roll forward to next row
var i2 = 0;
while (i2 < v.Length)
{
v[i2] += 1;
if (v[i2] > 1)
{
v[i2] = 0;
i2 += 1;
}
else
{
break;
}
}
if (i2 == v.Length)
{
done = true;
}
}
}
/// <summary>
/// Display a truth table and query the neural network.
/// </summary>
/// <param name="inputs">The inputs.</param>
/// <param name="output">The output.</param>
public static void TruthTable(IList<InputNeuron> inputs, RegularNeuron output)
{
var v = new double[inputs.Count];
var done = false;
while (!done)
{
for (var i = 0; i < inputs.Count; i++)
{
inputs[i].Value = v[i];
}
var o = output.Compute();
Console.WriteLine(v + " : " + o);
// Roll forward to next row
var i2 = 0;
while (i2 < v.Length)
{
v[i2] += 1;
if (v[i2] > 1)
{
v[i2] = 0;
i2 += 1;
}
else
{
break;
}
}
if (i2 == v.Length)
{
done = true;
}
}
}
/// <summary>
/// Create a neural network for AND.
/// </summary>
public static void ProcessAnd()
{
Console.WriteLine("Boolean AND");
var inputs = new List<InputNeuron>();
inputs.Add(new InputNeuron());
inputs.Add(new InputNeuron());
var output = new RegularNeuron(-1.5);
output.Parents.Add(new Connection(1, inputs[0]));
output.Parents.Add(new Connection(1, inputs[1]));
TruthTable(inputs, output);
}
/// <summary>
/// Create a neural network for XOR.
/// </summary>
public static void ProcessXor()
{
Console.WriteLine("Boolean XOR");
var inputs = new List<InputNeuron>();
inputs.Add(new InputNeuron());
inputs.Add(new InputNeuron());
var hidden1 = new List<RegularNeuron>();
hidden1.Add(new RegularNeuron(-0.5));
hidden1.Add(new RegularNeuron(-1.5));
hidden1[0].Parents.Add(new Connection(1, inputs[0]));
hidden1[0].Parents.Add(new Connection(1, inputs[1]));
hidden1[1].Parents.Add(new Connection(1, inputs[0]));
hidden1[1].Parents.Add(new Connection(1, inputs[1]));
var hidden2 = new RegularNeuron(0.5);
hidden2.Parents.Add(new Connection(-1, hidden1[1]));
var output = new RegularNeuron(-1.5);
output.Parents.Add(new Connection(1, hidden1[0]));
output.Parents.Add(new Connection(1, hidden2));
TruthTable(inputs, output);
}
