Delay-Distribution-Dependent Stability Criteria for BAM Neural Networks with Time-Varying Delays
| Main Authors: | J.H. Park, S. Lakshmanan, H.Y. Jung, S.M. Lee |
|---|---|
| Format: | Article |
| Bahasa: | eng |
| Terbitan: |
, 2013
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/1058521 |
Daftar Isi:
- This paper is concerned with the delay-distributiondependent stability criteria for bidirectional associative memory (BAM) neural networks with time-varying delays. Based on the Lyapunov-Krasovskii functional and stochastic analysis approach, a delay-probability-distribution-dependent sufficient condition is 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 simulation is given to demonstrate the usefulness and effectiveness of the proposed results.