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Delay-partitioning approach design for stochastic stability analysis of uncertain neutral-type neural networks with Markovian jumping parameters.

Authors :
Yin, Chun
Cheng, Yuhua
Huang, Xuegang
Zhong, Shou-ming
Li, Yuanyuan
Shi, Kaibo
Source :
Neurocomputing. Sep2016, Vol. 207, p437-449. 13p.
Publication Year :
2016

Abstract

This paper investigates the problem of stability analysis for uncertain neutral-type neural networks with Markovian jumping parameters and interval time-varying delays. By separating the delay interval into multiple subintervals, a Lyapunov–Krasovskii methodology is established, which contains triple and quadruple integrals. The time-varying delay is considered to locate into any subintervals, which is different from existing delay-partitioning methods. Based on the proposed delay-partitioning approach, a stability criterion is derived to reduce the conservatism. Numerical examples show the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09252312
Volume :
207
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
117373605
Full Text :
https://doi.org/10.1016/j.neucom.2016.05.025