Stability in cellular neural networks with a piecewise constant argument

AKHMET M., ARUĞASLAN ÇİNÇİN D., YILMAZ E.

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, cilt.233, sa.9, ss.2365-2373, 2010 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 233 Sayı: 9
  • Basım Tarihi: 2010
  • Doi Numarası: 10.1016/j.cam.2009.10.021
  • Dergi Adı: JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.2365-2373
  • Anahtar Kelimeler: 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
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

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.