A Note on “Global Robust Stability Criteria for Interval Delayed Neural Networks Via an LMI Approach”

Author

Shao, Jin-Liang ; Huang, Ting-Zhu

Author_Institution

Sch. of Appl. Math., Univ. of Electron. Sci. & Technol. of China, Chengdu

Volume

55

Issue

11

fYear

2008

Firstpage

1198

Lastpage

1202

Abstract

A recently reported result concerning the global exponential robust stability of delayed neural networks is revisited. It is shown by a counter example that the result is invalid because the proof is incorrect, and then a modified version is given. The paper also presents an improved sufficient condition for global exponential robust stability of the neural networks with unbounded activation functions and time-varying delays. Finally, a numerical simulation is given to show the effectiveness of the obtained result.

Keywords

asymptotic stability; delay systems; linear matrix inequalities; neurocontrollers; robust control; time-varying systems; LMI; delayed neural network; global exponential robust stability; time-varying delay; unbounded activation function; Counting circuits; Delay effects; Educational programs; Hydrogen; Linear matrix inequalities; Neural networks; Neurons; Robust stability; Robustness; Symmetric matrices; Dynamical interval neural networks; M-matrix; equilibrium analysis; global exponential robust stability;

fLanguage

English

Journal_Title

Circuits and Systems II: Express Briefs, IEEE Transactions on

Publisher

ieee

ISSN

1549-7747

Type

jour

DOI

10.1109/TCSII.2008.2008052

Filename

4703528