Stability criteria for BAM neural networks with leakage delays and probabilistic time-varying delays
- Stability criteria for BAM neural networks with leakage delays and probabilistic time-varying delays
- 정호열; 락쉬마난; 박주현; 이태희; R. Rakkiyappan[R. Rakkiyappan]
- GLOBAL EXPONENTIAL STABILITY; DISTRIBUTION-DEPENDENT STABILITY; ASYMPTOTIC STABILITY; NEUTRAL-TYPE; DISTRIBUTED DELAYS; ROBUST STABILITY; DISCRETE; TERM
- Issue Date
- ELSEVIER SCIENCE INC
- APPLIED MATHEMATICS AND COMPUTATION, v.219, no.17, pp.9408 - 9423
- This paper is concerned with the stability criteria for bidirectional associative memory (BAM) neural networks with leakage time delay and probabilistic time-varying delays. By establishing a stochastic variable with Bernoulli distribution, the information of probabilistic time-varying delay is transformed into the deterministic time-varying delay with stochastic parameters. Based on the Lyapunov-Krasovskii functional and stochastic analysis approach, delay-probability-distribution-dependent sufficient conditions are derived to achieve the globally asymptotically mean square stable of the considered BAM neural networks. The criteria are formulated in terms of a set of linear matrix inequalities (LMIs), which can be checked efficiently by use of some standard numerical packages. Finally, a numerical example and its simulations are given to demonstrate the usefulness and effectiveness of the proposed results. (c) 2013 Elsevier Inc. All rights reserved.
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