Geodesic
Stochastic stability analysis for a neutral-type neural networks with Markovian jumping parameters
Guo, Song1 ; Du, Bo2
1 Department of Mathematics, Huaiyin Normal University, Huaian, Jiangsu, 223300, P. R. China
2 Department of Mathematics, Huaiyin Normal University, Huaian , Jiangsu, 223300, P. R. China
Journal of nonlinear sciences and its applications, Tome 10 (2017) no. 7, p. 3409-3418.

Voir la notice de l'article provenant de la source International Scientific Research Publications

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.
DOI : 10.22436/jnsa.010.07.05
Classification : 34B15
Keywords: Markovian jumping parameters, linear matrix inequality, mean square stability.

Guo, Song 1 ; Du, Bo 2

1 Department of Mathematics, Huaiyin Normal University, Huaian, Jiangsu, 223300, P. R. China
2 Department of Mathematics, Huaiyin Normal University, Huaian , Jiangsu, 223300, P. R. China 
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Guo, Song; Du, Bo. Stochastic stability analysis  for a neutral-type neural networks with Markovian jumping parameters. Journal of nonlinear sciences and its applications, Tome 10 (2017) no. 7, p. 3409-3418. doi : 10.22436/jnsa.010.07.05. http://geodesic.mathdoc.fr/articles/10.22436/jnsa.010.07.05/

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