Global Exponential Robust Stability of High-Order Hopfield Neural Networks with S-Type Distributed Time Delays
Joint Authors
Wu, Bin
Zheng, Haiyong
Wang, Yangfan
Wei, Tengda
Wang, Linshan
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-26
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
By employing differential inequality technique and Lyapunov functional method, some criteria of global exponential robust stability for the high-order neural networks with S-type distributed time delays are established, which are easy to be verified with a wider adaptive scope.
American Psychological Association (APA)
Zheng, Haiyong& Wu, Bin& Wei, Tengda& Wang, Linshan& Wang, Yangfan. 2014. Global Exponential Robust Stability of High-Order Hopfield Neural Networks with S-Type Distributed Time Delays. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-492025
Modern Language Association (MLA)
Zheng, Haiyong…[et al.]. Global Exponential Robust Stability of High-Order Hopfield Neural Networks with S-Type Distributed Time Delays. Journal of Applied Mathematics No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-492025
American Medical Association (AMA)
Zheng, Haiyong& Wu, Bin& Wei, Tengda& Wang, Linshan& Wang, Yangfan. Global Exponential Robust Stability of High-Order Hopfield Neural Networks with S-Type Distributed Time Delays. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-492025
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-492025
