Global Exponential Robust Stability of Static Interval Neural Networks with Time Delay in the Leakage Term
Joint Authors
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-12
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
The stability of a class of static interval neural networks with time delay in the leakage term is investigated.
By using the method of M-matrix and the technique of delay differential inequality, we obtain some sufficient conditions ensuring the global exponential robust stability of the networks.
The results in this paper extend the corresponding conclusions without leakage delay.
An example is given to illustrate the effectiveness of the obtained results.
American Psychological Association (APA)
Chen, Guiying& Wang, Linshan. 2014. Global Exponential Robust Stability of Static Interval Neural Networks with Time Delay in the Leakage Term. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-512570
Modern Language Association (MLA)
Chen, Guiying& Wang, Linshan. Global Exponential Robust Stability of Static Interval Neural Networks with Time Delay in the Leakage Term. Journal of Applied Mathematics No. 2014 (2014), pp.1-6.
https://search.emarefa.net/detail/BIM-512570
American Medical Association (AMA)
Chen, Guiying& Wang, Linshan. Global Exponential Robust Stability of Static Interval Neural Networks with Time Delay in the Leakage Term. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-512570
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-512570