Comments on "A generalized LMI-based approach to the global asymptotic stability of delayed cellular neural networks"

Author

Hongtao Lu

Author_Institution

Dept. of Comput. Sci. & Eng., Shanghai Jiao Tong Univ., China

Volume

16

Issue

3

fYear

2005

fDate

5/1/2005 12:00:00 AM

Firstpage

778

Lastpage

779

Abstract

In this letter, we point out that the linear matrix inequality (LMI)-based criterion obtained in the above paper (Singh, IEEE Trans. Neural Netw., vol. 15, no. 1, p. 223-5, 2004) for the global exponential stability of the delayed neural networks can be simplified to a simpler but equivalent form and, thus, show that it is not necessary to have such complex form of condition in the above paper. As a result, we also answer the question raised by the author of the above paper.

Keywords

asymptotic stability; cellular neural nets; delays; linear matrix inequalities; delayed cellular neural network; exponential stability; global asymptotic stability; linear matrix inequality; Asymptotic stability; Cellular networks; Cellular neural networks; Computer science; Linear matrix inequalities; Mathematical analysis; Neural networks; Stability criteria; Symmetric matrices; Delayed cellular neural networks (DCNNs); global exponential stability; linear matrix inequality (LMI); Algorithms; Computer Simulation; Linear Models; Neural Networks (Computer); Numerical Analysis, Computer-Assisted; Time Factors;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/TNN.2005.844094

Filename

1427780