Canonical genetic learning of RBF networks is faster

摘要

We extend our previous theoretical results concerning functional equivalence of Gaussian RBF networks and test the proposed canonical genetic learning algorithm on two problems. In our experiments, canonical learning achieved the same error threshold about two times faster in comparison to standard GA.