New stability criteria for neural networks with distributed and probabilistic delays

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Yang, Rongni, Gao, Huijun, 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

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.

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Item type	Article
URI	https://vuir.vu.edu.au/id/eprint/4715
DOI	10.1007/s00034-008-9092-1
Official URL	http://dx.doi.org/10.1007/s00034-008-9092-1
Subjects	Historical > SEO Classification > 970109 Expanding Knowledge in Engineering Historical > Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM) Historical > FOR Classification > 0199 Other Mathematical Sciences Information Systems
Keywords	ResPubID17714, distributed delay, exponential stability, neural networks, Lyapunov–Krasovskii functional, time-varying delay
Citations in Scopus	37 - View on Scopus
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