Global dissipativity of Cohen-Grossberg neural networks with mixed delays

Author

Lou, Xuyang ; Ye, Qian ; Cui, Baotong

Author_Institution

Sch. of Commun. & Control Eng., Jiangnan Univ., Wuxi, China

Volume

1

fYear

2010

fDate

10-12 Aug. 2010

Firstpage

317

Lastpage

321

Abstract

This paper is concerned with global dissipativity of a general class of Cohen-Grossberg neural networks with both discrete time-varying delays and distributed time-varying delays. Based on the Lyapunov method, linear matrix inequality approach and some inequality techniques, some sufficient conditions are presented for checking the global dissipativity for Cohen- Grossberg neural networks with mixed time-varying delays, and characterizing the sets of global dissipativity and global exponentially dissipativity. Finally, some numerical simulations are given to show the effectiveness and feasibility of the results.

Keywords

Lyapunov methods; delays; discrete time systems; linear matrix inequalities; neural nets; time-varying systems; Cohen-Grossberg neural networks; Lyapunov method; discrete time-varying delays; distributed time-varying delays; global dissipativity; linear matrix inequality approach; Artificial neural networks; Asymptotic stability; Circuit stability; Delay; Numerical stability; Stability criteria; Cohen-Grossberg neural networks; Lyapunov functional; global attractive set; global dissipativity; mixed time-varying delays;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2010 Sixth International Conference on

Conference_Location

Yantai, Shandong

Print_ISBN

978-1-4244-5958-2

Type

conf

DOI

10.1109/ICNC.2010.5583925

Filename

5583925