Global Exponential Stability Criteria for Bidirectional Associative Memory Neural Networks with Time-Varying Delays
Joint Authors
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-05-30
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
The global exponential stability for bidirectional associative memory neural networks with time-varying delays is studied.
In our study, the lower and upper bounds of the activation functions are allowed to be either positive, negative, or zero.
By constructing new and improved Lyapunov-Krasovskii functional and introducing free-weighting matrices, a new and improved delay-dependent exponential stability for BAM neural networks with time-varying delays is derived in the form of linear matrix inequality (LMI).
Numerical examples are given to demonstrate that the derived condition is less conservative than some existing results given in the literature.
American Psychological Association (APA)
Thipcha, J.& Niamsup, Piyapong. 2013. Global Exponential Stability Criteria for Bidirectional Associative Memory Neural Networks with Time-Varying Delays. Abstract and Applied Analysis،Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-482138
Modern Language Association (MLA)
Thipcha, J.& Niamsup, Piyapong. Global Exponential Stability Criteria for Bidirectional Associative Memory Neural Networks with Time-Varying Delays. Abstract and Applied Analysis No. 2013 (2013), pp.1-13.
https://search.emarefa.net/detail/BIM-482138
American Medical Association (AMA)
Thipcha, J.& Niamsup, Piyapong. Global Exponential Stability Criteria for Bidirectional Associative Memory Neural Networks with Time-Varying Delays. Abstract and Applied Analysis. 2013. Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-482138
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-482138
