基于局部泛化误差模型的RBFNN的启发式训练方法

A Greedy Algorithm of RBFNN Based on Localized Generalization Error Model

研究如何应用吴永贤(W.W.Y.NG)提出的局部泛化误差模型来训练径向基函数神经网络(RBFNN),给出了一种训练RBFNN的启发式训练方法.实验表明,该方法成功解决了模型结果计算时间复杂度问题,同时RBFNN的训练精度也达到令人满意的结果.

This paper researches how to use the result of the localized generalization error model （LGEM） proposed by Doctor W. W. Y. NG to train RBFNN, and then proposes a greedy algorithm for training RBFNN based on LGEM. Experiment show that the greedy method solutions the problem of computation complexity of LGEM and the training accuracy has obtained good effect.