this.backpropagate = function(oAnn, aTargetOutput, nLearningRate) {
nLearningRate = nLearningRate || 1;
var oNode,
n = 0;
for (sNodeId in oAnn.getOutputGroup().getNodes()) {
oNode = oAnn.getOutputGroup().getNodes()[sNodeId];
oNode.setError(aTargetOutput[n] - oNode.getOutputValue());
n ++;
}
for (sNodeId in oAnn.getInputGroup().getNodes()) {
this.backpropagateNode(oAnn.getInputGroup().getNodes()[sNodeId], nLearningRate);
}
}
this.backpropagateNode = function(oNode, nLearningRate) {
var nError = oNode.getError(),
oOutputNodes,
oConn,
nWeight,
nOutputError,
nDerivative = oNode.getOutputValue() * (1 - oNode.getOutputValue()), // Derivative for sigmoid activation funciton
nInputValue = oNode.getInputValue(),
n;
if (nError === null /* Dont do the same node twice */ && oNode.hasOutputs()) {
nDerivative = nDerivative || 0.000000000000001;
nInputValue = nInputValue || 0.000000000000001;
oOutputNodes = oNode.getOutputNodes();
for (n=0; n<oOutputNodes.length; n++) {
nOutputError = this.backpropagateNode(oOutputNodes[n], nLearningRate);
oConn = oAnn.getConnection(oNode, oOutputNodes[n]);
nWeight = oConn.getWeight();
oConn.setWeight(nWeight + nLearningRate * nOutputError * nDerivative * nInputValue);
nError += nOutputError * nWeight;
}
oNode.setError(nError);
}
return oNode.getError();
}