Association Journal of CSIAM
Supervised by Ministry of Education of PRC
Sponsored by Xi'an Jiaotong University
ISSN 1005-3085  CN 61-1269/O1

Chinese Journal of Engineering Mathematics ›› 2016, Vol. 33 ›› Issue (1): 91-105.doi: 10.3969/j.issn.1005-3085.2016.01.009

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Mean Square Exponential Stability and Periodic Solutions of Stochastic Delay Cellular Neural Networks with Impulses

LI Hao1,  LI Yu2   

  1. 1- School of Mathematics and Statistics, Guangxi Normal University, Guilin 541004
    2- School of Economics, Xinyang Normal University, Xinyang 464000
  • Received:2014-03-25 Accepted:2015-03-09 Online:2016-02-15 Published:2016-04-15
  • Supported by:
    The Major Project of Foundation of Educational Committee of Henan Province (14B910001); the Planning Project of Philosophy and Social Science of Henan Province (2014BJJ069).

Abstract:

For a class of stochastic cellular neural networks with discrete delays and impu-lses (SDCNNswI), this paper discusses their exponential stability and the existence of periodic solutions. Firstly, Poincare contraction theory is utilized to derive the conditions to guarantee the existence of periodic solutions of SDCNNswI. Next, Lyapunov function, stochastic analysis theory and Young inequality are develo-ped to derive some theorems. These theorems provide several sufficient conditions to guarantee that the periodic solutions of SDCNNswI are mean square exponentially stable. These sufficient conditions only include the governing parameters of SDCNNswI and can be easily checked by simple algebraic methods. Finally, two examples are given to demonstrate the usefulness of the obtained results.

Key words: Brownian motion, Young inequality, It$\hat{\rm o}$ formula, Lyapunov function, exponential stability, cellular neural networks

CLC Number: