public void CreateNetWork(int NumberOfLayer, int NumberOfNeuronsPerlayer) // takes number of layer and how many neurons perlayer
{
for (int i = 0; i < NumberOfLayer; i++) // loops to create the layers
{
LayerNeurons = new List <RegularNeuron>();
newLayer = new NetWorkLayer(LayerNeurons, i); // creates a layer
for (int J = 0; J < NumberOfNeuronsPerlayer; J++) // loop to create the number of neuron for the newly created layer
{
regularNeuron = new RegularNeuron();
regularNeuron.Id = NeuronsID++;
newLayer.AddNeuronToLayer(regularNeuron);
}
NeuralNetwork.Add(newLayer);
}
//now we will connect the neurons from each layer to the neuron in the next layer
Random rand = new Random();//we will use a random number to give unique weights
int temp1;
int temp2;
for (int i = 0; i < NeuralNetwork.Count - 1; i++)
{
temp1 = i;
temp2 = i + 1;
foreach (RegularNeuron Neuron in NeuralNetwork[temp1].GetLayerNeuron())
{
// Neuron.Id = rand.Next(0, 100);
foreach (RegularNeuron NeuronTObeConnectedWith in NeuralNetwork[temp2].GetLayerNeuron())// for now we will standradize the connection weight to be 0.5
{
//NeuronTObeConnectedWith.Id = NeuronsID++;
Neuron.AddNeuron(NeuronTObeConnectedWith, (rand.Next(0, 100) / 10));// this connection weight is hard coded for now
}
}
//for testing
foreach (RegularNeuron Neuron in NeuralNetwork[i].GetLayerNeuron())
{
Neuron.Fire();
}
//foreach (RegularNeuron Neuron in NeuralNetwork[1].GetLayerNeuron())
//{
// Neuron.Fire();
//}
//foreach (RegularNeuron Neuron in NeuralNetwork[2].GetLayerNeuron())
//{
// Neuron.Fire();
//}
}
}
public void addLayerToEndOfNetWork()// for now we can only add a layer at the end of this neural network
{
NewLayernum = NeuralNetwork.Count;
newLayer = new NetWorkLayer(LayerNeurons, NewLayernum);
NeuralNetwork.Add(newLayer);
}
