public static bool Test1()
{
var i1 = new InputNode();
var i2 = new InputNode();
var h1 = new Perceptron(new Linear());
var h2 = new Perceptron(new Linear());
var h3 = new Perceptron(new Linear());
LinearWeight.Connect(i1, h1, 1.0);
LinearWeight.Connect(i1, h2, 1.0);
LinearWeight.Connect(i2, h2, 1.0);
LinearWeight.Connect(i2, h3, 1.0);
var ib = new BiasNode();
LinearWeight.Connect(ib, h1, 1.0);
LinearWeight.Connect(ib, h2, 2.0);
LinearWeight.Connect(ib, h3, 1.0);
var o = new Perceptron(new Linear());
LinearWeight.Connect(h1, o, 1.0);
LinearWeight.Connect(h2, o, -2.0);
LinearWeight.Connect(h3, o, 1.0);
var hb = new BiasNode();
var whbo = new LinearWeight(hb, o);
whbo[0] = 1.0;
var network = new GeneralNetwork(new List<InputNode> {i1, i2}, new List<INode>{o});
network.Forward(new[] { 0.0, 0.0 });
network.Forward(new[] { 1.0, 0.0 });
network.Forward(new[] { 0.0, 1.0 });
network.Forward(new[] { 1.0, 1.0 });
return true;
}
public static bool Test2()
{
var i1 = new InputNode();
var i2 = new InputNode();
var h1 = new Perceptron(new Heaviside(1.0));
var h2 = new Perceptron(new Heaviside(2.0));
var h3 = new Perceptron(new Heaviside(1.0));
LinearWeight.Connect(i1, h1, 1.0);
LinearWeight.Connect(i1, h2, 1.0);
LinearWeight.Connect(i2, h2, 1.0);
LinearWeight.Connect(i2, h3, 1.0);
var o = new Perceptron(new Linear());
LinearWeight.Connect(h1, o, 1.0);
LinearWeight.Connect(h2, o, -2.0);
LinearWeight.Connect(h3, o, 1.0);
var network = new GeneralNetwork(new List<InputNode> { i1, i2 }, new List<INode> { o });
network.Forward(new[] { 0.0, 0.0 });
network.Forward(new[] { 1.0, 0.0 });
network.Forward(new[] { 0.0, 1.0 });
network.Forward(new[] { 1.0, 1.0 });
return true;
}
