Stochastic stability analysis for a neutral-type neural networks with Markovian jumping parameters
- Department of Mathematics, Huaiyin Normal University, Huaian, Jiangsu, 223300, P. R. China.
- Department of Mathematics, Huaiyin Normal University, Huaian , Jiangsu, 223300, P. R. China.
In this paper, the stability problem is studied for a class of stochastic neutral-type neural networks with Markovian jumping
parameters. By using fixed point theorem, the existence and uniqueness of solution for the neural networks system are obtained.
Furthermore, based on the Lyapunov-Krasovskii functional, a linear matrix inequality (LMI) approach is developed to establish
sufficient conditions to guarantee the mean square stability of the neural networks. An example is given to show the effectiveness
of the proposed stability criterion.
Share and Cite
Song Guo, Bo Du, Stochastic stability analysis for a neutral-type neural networks with Markovian jumping parameters, Journal of Nonlinear Sciences and Applications, 10 (2017), no. 7, 3409--3418
Guo Song, Du Bo, Stochastic stability analysis for a neutral-type neural networks with Markovian jumping parameters. J. Nonlinear Sci. Appl. (2017); 10(7):3409--3418
Guo, Song, Du, Bo. "Stochastic stability analysis for a neutral-type neural networks with Markovian jumping parameters." Journal of Nonlinear Sciences and Applications, 10, no. 7 (2017): 3409--3418
- Markovian jumping parameters
- linear matrix inequality
- mean square stability.
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