Improved stability criteria for recurrent neural networks with interval time-varying delays via new Lyapunov functionals
SCIE
SCOPUS
- Title
- Improved stability criteria for recurrent neural networks with interval time-varying delays via new Lyapunov functionals
- Authors
- Il Lee, W; Lee, SY; Park, P
- Date Issued
- 2015-05-01
- Publisher
- ELSEVIER SCIENCE BV
- Abstract
- This paper considers the stability problem of recurrent neural networks with interval time-varying delays. Based on a new augmented Lyapunov-Krasovskii functional that contains four triple integral terms and additional terms obtained from the activation function condition, a stability condition is derived in terms of linear matrix inequalities (LMIs). Also, a further improved stability criterion is derived by bounding the derivative of a special case of the proposed Lyapunov-Krasovskii functional based on a new inequality proposed in Seuret and Gouaisbaut (2013) [27]. A numerical example shows the improvement of the proposed approach both in terms of computational complexity and conservatism. (C) 2015 Elsevier B.V. All rights reserved.
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/27130
- DOI
- 10.1016/J.NEUCOM.2014.12.040
- ISSN
- 0925-2312
- Article Type
- Article
- Citation
- NEUROCOMPUTING, vol. 155, page. 128 - 134, 2015-05-01
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