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Stability analysis of complex-valued neural networks with probabilistic time-varying delays.
- Source :
-
Neurocomputing . Jul2015, Vol. 159, p96-104. 9p. - Publication Year :
- 2015
-
Abstract
- In this paper, the stability of complex-valued neural networks with probabilistic time-varying delays is investigated. Two important integral inequalities that include Jensen׳s inequality as a special case are developed. By constructing proper Lyapunov–Krasovskii functional and employing inequality technique, several delay-distribution-dependent sufficient conditions are obtained to guarantee the global asymptotic and exponential stability of the addressed neural networks. These conditions are expressed in terms of complex-valued LMIs, which can be checked numerically using the effective YALMIP toolbox in MATLAB. An example with simulations is given to show the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09252312
- Volume :
- 159
- Database :
- Academic Search Index
- Journal :
- Neurocomputing
- Publication Type :
- Academic Journal
- Accession number :
- 101940934
- Full Text :
- https://doi.org/10.1016/j.neucom.2015.02.015