Convergence dynamics of hybrid bidirectional associative memory neural networks with distributed delays

被引：64
|
作者：
Liao, XF [1 ]
Wong, KW
Yang, SZ
机构：
[1] Chongqing Univ, Dept Comp Engn & Sci, Chongqing 400044, Peoples R China
[2] City Univ Hong Kong, Dept Comp Engn & Informat Technol, Hong Kong, Hong Kong, Peoples R China
[3] Chongqing Univ, Coll Commun, Chongqing 400044, Peoples R China
来源：
PHYSICS LETTERS A | 2003年 / 316卷 / 1-2期
关键词：
bidirectional associative memory; neural networks; distributed delays; global exponential stability;
D O I：
10.1016/S0375-9601(03)01113-7
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
In this Letter, the characteristics of the convergence dynamics of hybrid bidirectional associative memory neural networks with distributed transmission delays are studied. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the Lyapunov functionals are constructed and the generalized Halanay-type inequalities are employed to derive the delay-independent sufficient conditions under which the networks converge exponentially to the equilibria associated with temporally uniform external inputs. Some examples are given to illustrate the correctness of our results. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码：55 / 64
页数：10
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