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.

引用

页码：251 / 255

页数：5

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