public void AddInputNeuron(INeuron n)
{
NeuronInput inp = new NeuronInput();
inp.n = n;
inp.w = randomWeight();
inp.bias = 0;
inputs.Add(inp);
}
public void AddInputNeuron(INeuron n)
{
NeuronInput inp = new NeuronInput();
inp.n = n;
inp.w = randomWeight();
inp.bias = 0;
inputs.Add(inp);
}
public Neuron(bool nonlinear)
{
rand = new Random((int)(Neuron.randomSeed++));
Neuron.randomSeed = Neuron.randomSeed % 56264563;
inputs = new List<NeuronInput>();
NeuronInput inp = new NeuronInput();
inp.n = null;
inp.w = randomWeight();
inp.bias = 1;
inputs.Add(inp);
this.nonlinear = nonlinear;
}
public void LoadNN(string filename)
{
TextReader tr = new StreamReader(filename);
string line = tr.ReadLine();
List <INeuron> layer = null;
Neuron n = null;
int ni_counter = 0;
while (line != "E")
{
if (line == "M")
{
mlp = new List <List <INeuron> >();
}
if (line == "L")
{
layer = new List <INeuron>();
mlp.Add(layer);
}
if (line == "I")
{
layer.Add(new InputNeuron());
}
if ((line == "Pn") || (line == "P"))
{
n = new Neuron(true);
ni_counter = 0;
layer.Add(n);
}
if (line == "Pl")
{
n = new Neuron(false);
ni_counter = 0;
layer.Add(n);
}
if (line == "b")
{
string w = tr.ReadLine();
n.inputs[0].w = double.Parse(w, CultureInfo.InvariantCulture);
}
if (line == "w")
{
string w = tr.ReadLine();
NeuronInput ni = new NeuronInput();
ni.w = double.Parse(w, CultureInfo.InvariantCulture);
ni.n = mlp[mlp.Count - 2][ni_counter];
n.inputs.Add(ni);
ni_counter++;
}
line = tr.ReadLine();
}
tr.Close();
}
public Neuron(bool nonlinear)
{
rand = new Random((int)(Neuron.randomSeed++));
Neuron.randomSeed = Neuron.randomSeed % 56264563;
inputs = new List <NeuronInput>();
NeuronInput inp = new NeuronInput();
inp.n = null;
inp.w = randomWeight();
inp.bias = 1;
inputs.Add(inp);
this.nonlinear = nonlinear;
}
public double WeightSensibilityToError(int index, double error)
{
NeuronInput input = inputs[index];
double x;
if (input.n != null)
{
x = input.n.Output();
}
else
{
x = input.bias;
}
return(delta * x / error);
}
public void LoadNN(string filename)
{
TextReader tr = new StreamReader(filename);
string line = tr.ReadLine();
List<INeuron> layer = null;
Neuron n = null;
int ni_counter = 0;
while (line != "E")
{
if (line == "M") mlp = new List<List<INeuron>>();
if (line == "L")
{
layer = new List<INeuron>();
mlp.Add(layer);
}
if (line == "I") layer.Add(new InputNeuron());
if ((line == "Pn")||(line == "P"))
{
n = new Neuron(true);
ni_counter = 0;
layer.Add(n);
}
if (line == "Pl")
{
n = new Neuron(false);
ni_counter = 0;
layer.Add(n);
}
if (line == "b")
{
string w = tr.ReadLine();
n.inputs[0].w = double.Parse(w, CultureInfo.InvariantCulture);
}
if (line == "w")
{
string w = tr.ReadLine();
NeuronInput ni = new NeuronInput();
ni.w = double.Parse(w, CultureInfo.InvariantCulture);
ni.n = mlp[mlp.Count - 2][ni_counter];
n.inputs.Add(ni);
ni_counter++;
}
line = tr.ReadLine();
}
tr.Close();
}