Global Exponential Stability of Fuzzy Neural Networks with Unbounded Delay and Variable Coefficients

Author

Jin, Songhe ; Ren, Dianbo ; Zhang, Jiye

Author_Institution

Sch. of Comput. & Commun. Eng., Zhengzhou Univ. of Light Ind., Zhengzhou, China

fYear

2009

fDate

19-20 Dec. 2009

Firstpage

1

Lastpage

4

Abstract

In this brief, the global exponential stability of fuzzy cellular neural networks(FCNNs) with variable coefficients and unbounded delays was investigated. Without assuming the boundedness and differentiability of the activation functions, based on the properties of M-matrix, by constructing vector Lyapunov functions and applying differential inequalities, the sufficient condition for globally exponential stability of the fuzzy cellular neural networks with variable coefficients and unbounded delays was obtained.

Keywords

Lyapunov methods; asymptotic stability; cellular neural nets; delays; fuzzy neural nets; matrix algebra; M-matrix; differentiability; differential inequalities; fuzzy cellular neural networks; global exponential stability; unbounded delay; variable coefficients; vector Lyapunov functions; Asymptotic stability; Automotive engineering; Cellular neural networks; Computer networks; Delay effects; Fuzzy neural networks; Image processing; Lyapunov method; Neural networks; Sufficient conditions;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4994-1

Type

conf

DOI

10.1109/ICIECS.2009.5363119

Filename

5363119