Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays
Joint Authors
Source
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-12-18
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
A class of interval neural networks with time-varying delays and distributed delays is investigated.
By employing H-matrix and M-matrix theory, homeomorphism techniques, Lyapunov functional method, and linear matrix inequality approach, sufficient conditions for the existence, uniqueness, and global robust exponential stability of the equilibrium point to the neural networks are established and some previously published results are improved and generalized.
Finally, some numerical examples are given to illustrate the effectiveness of the theoretical results.
American Psychological Association (APA)
Du, Yanke& Xu, Rui. 2012. Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays. Abstract and Applied Analysis،Vol. 2012, no. 2012, pp.1-18.
https://search.emarefa.net/detail/BIM-487918
Modern Language Association (MLA)
Du, Yanke& Xu, Rui. Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays. Abstract and Applied Analysis No. 2012 (2012), pp.1-18.
https://search.emarefa.net/detail/BIM-487918
American Medical Association (AMA)
Du, Yanke& Xu, Rui. Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays. Abstract and Applied Analysis. 2012. Vol. 2012, no. 2012, pp.1-18.
https://search.emarefa.net/detail/BIM-487918
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-487918