The almost periodic solution of Lotka-Volterra recurrent neural networks with delays

被引:14
|
作者
Liu, Yiguang [1 ]
Liu, Bingbing [2 ]
Ling, Sai Ho [3 ]
机构
[1] Sichuan Univ, Sch Engn & Comp Sci, Vis & Image Proc Lab, Chengdu 610064, Peoples R China
[2] ASTAR, Data Storage Inst, Singapore 138632, Singapore
[3] Univ Technol Sydney, Fac Engn & Informat Technol, Ctr Hlth Technol, Sydney, NSW 2007, Australia
关键词
Lotka-Volterra recurrent neural networks; Almost periodic solution; Lyapunov functional; Stability; TIME DELAYS; SYSTEM; EXISTENCE; MODELS;
D O I
10.1016/j.neucom.2010.11.009
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
By the fixed-point theorem subject to different polyhedrons and some inequalities (e.g., the inequality resulted from quadratic programming), we obtain three theorems for the Lotka-Volterra recurrent neural networks having almost periodic coefficients and delays. One of the three theorems can only ensure the existence of an almost periodic solution, whose existence and uniqueness the other two theorems are about. By using Lyapunov function, the sufficient condition guaranteeing the global stability of the solution is presented. Furthermore, two numerical examples are employed to illustrate the feasibility and validity of the obtained criteria. Compared with known results, the networks model is novel, and the results are extended and improved. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:1062 / 1068
页数:7
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