Method for balancing winning chances of competitive neurons
Zhanjie Guo · Jisuanji gongcheng yu sheji · 2009
Nowadays competitive neural network has been widely used in artificial intelligence and other aspects.But there is a problem exists in the competition neural networks which is called blind spot:Some neurons have never won in competition so become dead neurons.This problem only causes a waste of neurons,but also results in the training error too great to meet the request of training precision and hardly completes the task of classification or clustering.Aiming at this problem,the learning vector quantization neural networks is probed into,settles the problem of large training error properly when it comes to bind spot in such networks by inducting threshold learning rules and balancing the neurons' winning chances.Finally emulational experiment proves the validity of this method.