Improved Stability Criteria of Static Recurrent Neural Networks with a Time-Varying Delay
Joint Authors
Ding, Lei
Wang, Wei
Yu, Fei
Zeng, Hongbing
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-24
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
This paper investigates the stability of static recurrent neural networks (SRNNs) with a time-varying delay.
Based on the complete delay-decomposing approach and quadratic separation framework, a novel Lyapunov-Krasovskii functional is constructed.
By employing a reciprocally convex technique to consider the relationship between the time-varying delay and its varying interval, some improved delay-dependent stability conditions are presented in terms of linear matrix inequalities (LMIs).
Finally, a numerical example is provided to show the merits and the effectiveness of the proposed methods.
American Psychological Association (APA)
Ding, Lei& Zeng, Hongbing& Wang, Wei& Yu, Fei. 2014. Improved Stability Criteria of Static Recurrent Neural Networks with a Time-Varying Delay. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1049430
Modern Language Association (MLA)
Ding, Lei…[et al.]. Improved Stability Criteria of Static Recurrent Neural Networks with a Time-Varying Delay. The Scientific World Journal No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-1049430
American Medical Association (AMA)
Ding, Lei& Zeng, Hongbing& Wang, Wei& Yu, Fei. Improved Stability Criteria of Static Recurrent Neural Networks with a Time-Varying Delay. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1049430
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049430