private float Function2DNet(float x)
{
net.Inputs[0].value = (x - net.biasX[0]) / net.scaleX[0];
net.Calculate();
return(net.LastNeuronGroup.Neurons[0].OUT * net.scaleY[0] + net.biasY[0]);
}
private void посчитатьВыходСетиToolStripMenuItem_Click(object sender, EventArgs e)
{
net.Calculate();
for (int i = 0; i < net.OutputsCount; i++)
{
OutputGridView.Rows[i].Cells[1].Value = net.LastNeuronGroup.Neurons[i].OUT;
}
}
private void button1_Click(object sender, EventArgs e)
{
net.Calculate();
nGraphics.Refresh();
}
private void CalculateNet(object sender, EventArgs e)
{
net.Calculate();
Refresh();
}
