New theorems on global convergence of some dynamical systems

被引：71
作者：
Chen, TP [1 ]
Amari, S
机构：
[1] Fudan Univ, Dept Math, Shanghai 200433, Peoples R China
[2] RIKEN, Brain Sci Inst, Wako, Saitama 35101, Japan
来源：
NEURAL NETWORKS | 2001年 / 14卷 / 03期
关键词：
recurrent neural networks; stability;
D O I：
10.1016/S0893-6080(00)00100-3
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we discuss dynamical behaviors of recurrently asymmetrically connected neural networks. We propose a new approach to study global convergence of the networks. Better test conditions for global convergence are given. (C) 2001 Elsevier Science Ltd. All rights reserved.
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页码：251 / 255
页数：5
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