IJPAM: Volume 95, No. 1 (2014)

AN IMPROVED EXPONENTIAL STABILITY OF SWITCHED
NEURAL NETWORKS WITH INTERVAL
TIME-VARYING DELAY

Manlika Rajchakit$^1$, Grienggrai Rajchakit$^2$
$^{1,2}$Department of Mathematics and Statistics
Maejo University
Chiangmai, 50290, THAILAND


Abstract. This paper studies the problem for exponential stability of switched neural networks with interval time-varying delay. The time delay is a continuous function belonging to a given interval, but not necessary to be differentiable. By constructing a set of augmented Lyapunov-Krasovskii functional combined with Newton-Leibniz formula, a switching rule and switching design for exponential stability for of switched recurrent neural networks with interval time-varying delay is designed via linear matrix inequalities, and new sufficient conditions for the exponential stability of switched recurrent neural networks with interval time-varying delay via linear matrix inequalities(LMIs).

Received: January 20, 2014

AMS Subject Classification: 92B05, 93D20

Key Words and Phrases: neural networks, switching design, exponential stability, interval time-varying delays, Lyapunov function, linear matrix inequalities

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DOI: 10.12732/ijpam.v95i1.7 How to cite this paper?

Source:
International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2014
Volume: 95
Issue: 1
Pages: 57 - 67


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