public NeuroNetwork()
{
data = new Dictionary <int, INeuroLayer>();
NeuroLayer L1 = new NeuroLayer(1, 3, 3, LayerRole.Input);
NeuroLayer L2 = new NeuroLayer(2, 3, 3, LayerRole.Inner);
NeuroLayer L3 = new NeuroLayer(3, 3, 3, LayerRole.Output);
L1.NeuroImpulse += L2.ProcessData;
L2.NeuroImpulse += L3.ProcessData;
data.Add(L1.LayerID, L1);
data.Add(L2.LayerID, L2);
data.Add(L3.LayerID, L3);
layerFirst = L1;
layerLast = L3;
Dendrites = layerFirst.Dendrites;
SynapticKnobs = layerLast.SynapticKnobs;
layerLast.NeuroImpulse += (knobs) =>
{ NeuroImpulse?.Invoke(knobs); };
}
private void ProcessInputData(IEnumerable <INeuroTransmitter> incoming)
{
// 1) In the begining we must accept incoming data values
foreach (INeuroTransmitter item in incoming)
{
if (input.TryGetValue(item.ItemID, out NeuroSignal signalIn))
{
signalIn.Value = item.Value;
}
}
// 2) Next, we must calculate outputs
foreach (NeuroItem core in nucleus.Values)
{
core.ProcessData();
if (output.TryGetValue(core.Number, out NeuroSignal signalOut))
{
signalOut.Value = core.Axon.Value;
}
}
// 3) Then, we must notify next level or user class
NeuroImpulse?.Invoke(SynapticKnobs);
}