| Author Name | Affiliation | | ZHU En-wen | School of Mathematics and Computational Science,Changsha University of Science and Technology,Changsha 410076,China
School of Mathematics and Computational Science,Xiangtan University,Xiangtan 411105,China | | WANG Yong | Dept.of Mathematics,Harbin Institute of Technology, Harbin 150001,China | | ZHANG Han-jun | School of Mathematics and Computational Science,Xiangtan University,Xiangtan 411105,China | | ZOU Jie-zhong | School of Mathematics,Central South University,Changsha 410075,China |
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| Abstract: |
| To establish easily proved conditions under which the random delayed recurrent neural network with Markovian switching is mean-square stability,the evolution of the delay was modeled by a continuous-time homogeneous Markov process with a finite number of states.By employing Lyapunov-Krasovskii functionals and conducting stochastic analysis,a linear matrix inequality (LMI) approach was developed to derive the criteria for mean-square stability,which can be readily checked by some standard numerical packages such as the Matlab LMI Toolbox.A numerical example was exploited to show the usefulness of the derived LMI-based stability conditions. |
| Key words: recurrent neural networks mean-square stability random delay Markovian switching linear matrix inequality |
| DOI：10.11916/j.issn.1005-9113.2009.05.017 |
| Clc Number:O781;O734 |
| Fund: |
