Research Repository

New stability criteria for neural networks with distributed and probabilistic delays

Yang, Rongni and Gao, Huijun and Lam, James and Shi, Peng (2009) New stability criteria for neural networks with distributed and probabilistic delays. Circuits Systems and Signal Processing, 28. pp. 505-522. ISSN 0278-081X

Full text for this resource is not available from the Research Repository.

Abstract

This paper is concerned with the stability analysis of neural networks with distributed and probabilistic delays. The probabilistic delay satisfies a certain probability distribution. By introducing a stochastic variable with a Bernoulli distribution, the neural network with random time delays is transformed into one with deterministic delays and stochastic parameters. New conditions for the exponential stability of such neural networks are obtained by employing new Lyapunov–Krasovskii functionals and novel techniques for achieving delay dependence. The proposed conditions reduce the conservatism by considering not only the range of the time delays, but also the probability distribution of their variation. A numerical example is provided to show the advantages of the proposed techniques.

Item Type: Article
Uncontrolled Keywords: ResPubID17714, distributed delay, exponential stability, neural networks, Lyapunov–Krasovskii functional, time-varying delay
Subjects: SEO Classification > 970109 Expanding Knowledge in Engineering
Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM)
FOR Classification > 0199 Other Mathematical Sciences Information Systems
Depositing User: VUIR
Date Deposited: 14 Jun 2011 06:53
Last Modified: 01 May 2012 02:22
URI: http://vuir.vu.edu.au/id/eprint/4715
DOI: 10.1007/s00034-008-9092-1
ePrint Statistics: View download statistics for this item
Citations in Scopus: 21 - View on Scopus

Repository staff only

View Item View Item

Search Google Scholar