The stability of the analog Hopfield neural network with iterative dynamics

被引：0
|
作者：
Wang, LP [1 ]
机构：
[1] Deakin Univ, Sch Comp & Math, Clayton, Vic 3168, Australia
来源：
1997 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT PROCESSING SYSTEMS, VOLS 1 & 2 | 1997年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We first present an example which shows that a general dynamic system with an infinite number of fixed points may never stabilize, even when there exists a Lyapunov function which strictly decreases along all possible trajectories. We then explain why the analog Hopfield neural network with iterative dynamics always converges to a fixed point, regardless how many fixed points it has.
引用
收藏
页码：449 / 452
页数：4
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