Asymptotic Stability of Stochastic Delayed Recurrent Neural Networks with Impulsive Effects
R. Sakthivel (),
R. Samidurai and
S. M. Anthoni
Additional contact information
R. Sakthivel: Sungkyunkwan University
R. Samidurai: Periyar University
S. M. Anthoni: Anna University Coimbatore
Journal of Optimization Theory and Applications, 2010, vol. 147, issue 3, No 11, 583-596
Abstract:
Abstract In this paper, the asymptotic stability for a class of stochastic neural networks with time-varying delays and impulsive effects are considered. By employing the Lyapunov functional method, combined with linear matrix inequality optimization approach, a new set of sufficient conditions are derived for the asymptotic stability of stochastic delayed recurrent neural networks with impulses. A numerical example is given to show that the proposed result significantly improve the allowable upper bounds of delays over some existing results in the literature.
Keywords: Stochastic delayed recurrent neural networks; Impulsive effects; Linear matrix inequality optimization approach; Global asymptotic stability; Lyapunov functional (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://link.springer.com/10.1007/s10957-010-9728-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:147:y:2010:i:3:d:10.1007_s10957-010-9728-8
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2
DOI: 10.1007/s10957-010-9728-8
Access Statistics for this article
Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull
More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().