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Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay
Joint Authors
Wang, Xiuling
Liu, Yonghua
Lan, Hongli
Luo, Wenguang
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-02-28
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
The problem of global exponential stability for recurrent neural networks with time-varying delay is investigated.
By dividing the time delay interval [0,τ(t)] into K+1 dynamical subintervals, a new Lyapunov-Krasovskii functional is introduced; then, a novel linear-matrix-inequality (LMI-) based delay-dependent exponential stability criterion is derived, which is less conservative than some previous literatures (Zhang et al., 2005; He et al., 2006; and Wu et al., 2008).
An illustrate example is finally provided to show the effectiveness and the advantage of the proposed result.
American Psychological Association (APA)
Luo, Wenguang& Wang, Xiuling& Liu, Yonghua& Lan, Hongli. 2013. Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay. Abstract and Applied Analysis،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-479946
Modern Language Association (MLA)
Luo, Wenguang…[et al.]. Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay. Abstract and Applied Analysis No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-479946
American Medical Association (AMA)
Luo, Wenguang& Wang, Xiuling& Liu, Yonghua& Lan, Hongli. Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay. Abstract and Applied Analysis. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-479946
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-479946