New global asymptotic stability criterion for neural networks with discrete and distributed delays
Shi, Peng, Zhang, Jinhui, Qiu, Jiqing and Xing, Li’nan (2007) New global asymptotic stability criterion for neural networks with discrete and distributed delays. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering , 221 (1). pp. 129-135. ISSN 0959-6518
Abstract
This paper investigates the problem of global asymptotic stability for a class of neural networks with time-varying and distributed delays. By the Lyapunov-Krasovskii functional approach, a new delay-dependent stability criterion is derived in terms of linear matrix inequalities (LMIs). The new stability condition does not require the time delay function to be continuously differentiable and its derivative to be less than 1, and it allows the time delay to be a fast time-varying function. Simulation examples are given to demonstrate the effectiveness of the developed techniques.
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Item type | Article |
URI | https://vuir.vu.edu.au/id/eprint/3406 |
DOI | 10.1243/09596518JSCE287 |
Official URL | http://pii.sagepub.com/content/221/1/129.full.pdf |
Subjects | Historical > Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM) Historical > FOR Classification > 0913 Mechanical Engineering Historical > FOR Classification > 0199 Other Mathematical Sciences Information Systems |
Keywords | ResPubID18803, neural networks, time-varying delay, distributed delay, global asymptotic stability, linear matrix inequalities |
Citations in Scopus | 21 - View on Scopus |
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