- Title
- Dynamical analysis of neural networks with time-varying delays using the LMI approach
- Creator
- Lakshmanan, Shanmugam; Lim, Cheepeng; Bhatti, Asim; Gao, David; Nahavandi, Saeid
- Date
- 2015
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/99945
- Identifier
- vital:10448
- Identifier
-
https://doi.org/10.1007/978-3-319-26555-1_34
- Identifier
- ISBN:03029743 (ISSN); 9783319265544 (ISBN)
- Abstract
- This study is concerned with the delay-range-dependent stability analysis for neural networks with time-varying delay and Markovian jumping parameters. The time-varying delay is assumed to lie in an interval of lower and upper bounds. The Markovian jumping parameters are introduced in delayed neural networks, which are modeled in a continuous-time along with finite-state Markov chain. Moreover, the sufficient condition is derived in terms of linear matrix inequalities based on appropriate Lyapunov-Krasovskii functionals and stochastic stability theory, which guarantees the globally asymptotic stable condition in the mean square. Finally, a numerical example is provided to validate the effectiveness of the proposed conditions. © Springer International Publishing Switzerland 2015.
- Publisher
- Springer Verlag
- Relation
- 22nd International Conference on Neural Information Processing, ICONIP 2015; Istanbul, Turkey; 9th-12th November 2015 Vol. 9491, p. 297-305
- Rights
- Copyright © Springer International Publishing Switzerland 2015.
- Rights
- This metadata is freely available under a CCO license
- Subject
- 08 Information and Computing Sciences; Interval time-varying delay; Linear matrix inequality; Neural networks; Stability
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