Boundedness, periodic solutions and global stability for cellular neural networks with variable coefficients and infinite delays

被引:24
|
作者
Jiang, Haijun [1 ]
Teng, Zhidong [1 ]
机构
[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Peoples R China
关键词
Cellular neural networks; Infinite delays; Variable coefficients; Boundedness; Globally asymptotic stability; Globally exponential stability; Periodic solution; Lyapunov functional; Banach space C-g(R_); TIME-VARYING DELAYS; CONTINUOUSLY DISTRIBUTED DELAYS; FUNCTIONAL-DIFFERENTIAL EQUATIONS; ASSOCIATIVE MEMORY NETWORKS; EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; EXISTENCE;
D O I
10.1016/j.neucom.2008.11.010
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 consider the cellular neural networks with variable coefficients and infinite distributed delays. By introducing the phase space C-g(R_) and applying Lyapunov functional method and Young inequality technique, we first establish a series of criteria on the boundedness, globally asymptotic stability and globally exponential stability. Furthermore, by applying these results and combining the existence theorems of periodic solutions for general functional differential equations with infinite delays, we establish the existence of periodic solutions and its globally asymptotic stability and globally exponential stability for the periodic cellular neural networks with infinite distributed delays. At last, as a special case, we apply these results to the autonomous cellular neural networks with infinite distributed delays and the existence, uniqueness and global stability of equilibrium point are established. (c) 2008 Elsevier B.V. All rights reserved.
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页码:2455 / 2463
页数:9
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