Global robust stability of delayed neural networks with discontinuous activation functions
Global robust stability of delayed neural networks with discontinuous activation functions
- Author(s): Y. Wang ; Y. Zuo ; L. Huang ; C. Li
- DOI: 10.1049/iet-cta:20070323
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- Author(s): Y. Wang 1 ; Y. Zuo 1 ; L. Huang 2 ; C. Li 1, 3
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View affiliations
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Affiliations:
1: College of Electric and Information Technology, Hunan University, Changsha, People's Republic of China
2: College of Mathematics and Econometrics, Hunan University, Changsha, People's Republic of China
3: Department of Mathematics and Computer Science, Guang Dong University of Business Studies, Guangzhou, People's Republic of China
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Affiliations:
1: College of Electric and Information Technology, Hunan University, Changsha, People's Republic of China
- Source:
Volume 2, Issue 7,
July 2008,
p.
543 – 553
DOI: 10.1049/iet-cta:20070323 , Print ISSN 1751-8644, Online ISSN 1751-8652
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© The Institution of Engineering and Technology
Published
The authors consider the problem of global robust stability of delayed neural networks with discontinuous activation functions. The stability conditions are given in terms of a linear matrix inequalities, and based on the Lyapunov–Krasovskii stability theory. The results are brand new and original compared with the previous literature. Two numerical examples are given to show the effectiveness of the results.
Inspec keywords: delays; Lyapunov methods; stability; neural nets; linear matrix inequalities
Other keywords:
Subjects: Neural nets (theory); Algebra
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