New Improved Exponential Stability Criteria for Discrete-Time Neural Networks with Time-Varying Delay
Joint Authors
Lü, Shu
Liu, Zixin
Ye, Mao
Zhong, Shouming
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2009, Issue 2009 (31 Dec. 2009), pp.1-23, 23 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2009-07-22
Country of Publication
Egypt
No. of Pages
23
Main Subjects
Abstract EN
The robust stability of uncertain discrete-time recurrent neural networks with time-varying delay is investigated.
By decomposing some connection weight matrices, new Lyapunov-Krasovskii functionals are constructed, and serial new improved stability criteria are derived.
These criteria are formulated in the forms of linear matrix inequalities (LMIs).
Compared with some previous results, the new results are less conservative.
Three numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed method.
American Psychological Association (APA)
Liu, Zixin& Lü, Shu& Zhong, Shouming& Ye, Mao. 2009. New Improved Exponential Stability Criteria for Discrete-Time Neural Networks with Time-Varying Delay. Discrete Dynamics in Nature and Society،Vol. 2009, no. 2009, pp.1-23.
https://search.emarefa.net/detail/BIM-505300
Modern Language Association (MLA)
Liu, Zixin…[et al.]. New Improved Exponential Stability Criteria for Discrete-Time Neural Networks with Time-Varying Delay. Discrete Dynamics in Nature and Society No. 2009 (2009), pp.1-23.
https://search.emarefa.net/detail/BIM-505300
American Medical Association (AMA)
Liu, Zixin& Lü, Shu& Zhong, Shouming& Ye, Mao. New Improved Exponential Stability Criteria for Discrete-Time Neural Networks with Time-Varying Delay. Discrete Dynamics in Nature and Society. 2009. Vol. 2009, no. 2009, pp.1-23.
https://search.emarefa.net/detail/BIM-505300
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-505300
