Stability in cellular neural networks with a piecewise constant argument

被引：45
作者：
Akhmet, M. U. [1 ,2 ]
Arugaslan, D. [3 ]
Yilmaz, E. [2 ]
机构：
[1] Middle E Tech Univ, Dept Math, TR-06531 Ankara, Turkey
[2] Middle E Tech Univ, Inst Appl Math, TR-06531 Ankara, Turkey
[3] Suleyman Demirel Univ, Dept Math, TR-32260 Isparta, Turkey
来源：
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS | 2010年 / 233卷 / 09期
关键词：
Cellular neural networks; Differential equations with a piecewise constant argument of generalized type; Lyapunov-Razumikhin technique; Method of Lyapunov functions; Linear matrix inequality; GLOBAL ASYMPTOTIC STABILITY; DIFFERENTIAL-EQUATIONS; EXPONENTIAL STABILITY; CONTINUOUS-TIME;
D O I：
10.1016/j.cam.2009.10.021
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, by using the concept of differential equations with piecewise constant arguments of generalized type [1-4], a model of cellular neural networks (CNNs) [5,6] is developed. The Lyapunov-Razumikhin technique is applied to find sufficient conditions for the uniform asymptotic stability of equilibria. Global exponential stability is investigated by means of Lyapunov functions. An example with numerical simulations is worked out to illustrate the results. (C) 2009 Elsevier B.V. All rights reserved.
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收藏
页码：2365 / 2373
页数：9
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