摘要
通过引入样本模式向量割、割等价及割互补的概念,研究了基于外积取等准则的联想记忆神经网络在同步运行方式下的收敛性,得出对任意输入网络至多两步收敛.
By introducing concepts of cut,cut equivalence and cut complement, the convergence of associative memory neural networks based on outer product equstion learning rule under synchronous operation mode is studied. It is proved that the number of iterations required to achieve convergence is at most two.
出处
《电子学报》
EI
CAS
CSCD
北大核心
1997年第4期89-91,共3页
Acta Electronica Sinica
基金
国家教委9361403号博士点基金
关键词
神经网络
外积取等准则
收敛性
割
割等价
Neural networks, Outer product equation rule, Convergence, Cut, Cut equivalence