public TargetNetwork(double[][,] NewW, int m, int n, int acts, int newH)
{
h = newH;
I = new InpN[(m * n)];
O = new OutN[(m * n * acts)];
H[0] = new Neuron[h];
H[1] = new Neuron[h];
for (int i = 0; i < m * n; i++)
{
I[i] = new InpN(Rand.NextDouble());
}
for (int i = 0; i < m * n * acts; i++)
{
O[i] = new OutN(Rand.NextDouble());
}
for (int i = 0; i < h; i++)
{
H[0][i] = new Neuron(Rand.NextDouble());
H[1][i] = new Neuron(Rand.NextDouble());
}
W = NewW;
M = m;
N = n;
ACTS = acts;
}
public NeuralNetwork(int m, int n, int acts, bool[] Rules, bool[,] Allowed, bool[,] Restricted)
{
// Инициализация нейронов, весов и нейросети цели
I = new InpN[(m * n)];
O = new OutN[(m * n * acts)];
H[0] = new Neuron[h];
H[1] = new Neuron[h];
for (int i = 0; i < m * n; i++)
{
I[i] = new InpN(Rand.NextDouble());
}
for (int i = 0; i < m * n * acts; i++)
{
O[i] = new OutN(Rand.NextDouble());
}
for (int i = 0; i < h; i++)
{
H[0][i] = new Neuron(Rand.NextDouble());
H[1][i] = new Neuron(Rand.NextDouble());
}
dW[0] = new double[m * n + 1, h];
dW[1] = new double[h + 1, h];
dW[2] = new double[h + 1, m *n *acts];
W[0] = new double[m * n + 1, h];
W[1] = new double[h + 1, h];
W[2] = new double[h + 1, m *n *acts];
for (int i = 0; i < (m * n) + 1; i++)
{
for (int j = 0; j < h; j++)
{
W[0][i, j] = Rand.Next(-10, 10) / 10.0;
}
}
for (int i = 0; i < h + 1; i++)
{
for (int j = 0; j < h; j++)
{
W[1][i, j] = Rand.Next(-10, 10) / 10.0;
}
}
for (int i = 0; i < h + 1; i++)
{
for (int j = 0; j < (m * n * acts); j++)
{
W[2][i, j] = Rand.Next(-10, 10) / 10.0;
}
}
M = m;
N = n;
ACTS = acts;
TN = new TargetNetwork(W, M, N, ACTS, h);
this.Rules = Rules;
this.Allowed = Allowed;
this.Restricted = Restricted;
}
