/// <summary>
/// Overridden.Method that constructs network topology.
/// </summary>
protected override void CreateNetwork()
{
nodes = new NeuroNode[NodesCount];
links = new NeuroLink[LinksCount];
var cnt = 0;
for (var i = 0; i < InputNodesCount; i++)
{
nodes[cnt] = new InputNode();
cnt++;
}
firstMiddleNode = cnt;
for (var i = 1; i < (layersCount - 1); i++)
{
for (var j = 0; j < nodesInLayer[i]; j++)
{
nodes[cnt] = new BackPropagationMiddleNode(LearningRate, momentum);
cnt++;
}
}
firstOutputNode = cnt;
for (var i = 0; i < OutputNodesCount; i++)
{
nodes[cnt] = new BackPropagationOutputNode(LearningRate, momentum);
cnt++;
}
for (var i = 0; i < LinksCount; i++)
{
links[i] = CreateLink();
}
cnt = 0;
var l1 = 0;
var l2 = firstMiddleNode;
for (var i = 0; i < (layersCount - 1); i++)
{
for (var j = 0; j < nodesInLayer[i + 1]; j++)
{
for (var k = 0; k < nodesInLayer[i]; k++)
{
nodes[l1 + k].LinkTo(nodes[l2 + j], links[cnt]);
cnt++;
}
}
l1 = l2;
l2 += nodesInLayer[i + 1];
}
}
/// <summary>
/// Overridden.Method that constructs network topology.
/// </summary>
protected override void CreateNetwork()
{
nodes = new NeuroNode[NodesCount];
links = new NeuroLink[LinksCount];
var cnt = 0;
for (var i = 0; i < InputNodesCount; i++)
{
nodes[cnt] = new InputNode();
cnt++;
}
firstMiddleNode = cnt;
for (var i = 1; i < (layersCount - 1); i++)
for (var j = 0; j < nodesInLayer[i]; j++)
{
nodes[cnt] = new BackPropagationMiddleNode(LearningRate, momentum);
cnt++;
}
firstOutputNode = cnt;
for (var i = 0; i < OutputNodesCount; i++)
{
nodes[cnt] = new BackPropagationOutputNode(LearningRate, momentum);
cnt++;
}
for (var i = 0; i < LinksCount; i++)
links[i] = CreateLink();
cnt = 0;
var l1 = 0;
var l2 = firstMiddleNode;
for (var i = 0; i < (layersCount - 1); i++)
{
for (var j = 0; j < nodesInLayer[i + 1]; j++)
for (var k = 0; k < nodesInLayer[i]; k++)
{
nodes[l1 + k].LinkTo(nodes[l2 + j], links[cnt]);
cnt++;
}
l1 = l2;
l2 += nodesInLayer[i + 1];
}
}
