RESEARCH ARTICLE


Stability Analysis for Stochastic Markovian Jumping Neural Networks with Leakage Delay



Yajun Li1, *, Xisheng Dai2, Wenping Xiao1, Like Jiao1
1 Institute of Electronics and Information Engineering, Shunde Polytechnic, Foshan, 528300, China
2 School of Electrical and Information Engineering, Guangxi University of Science and Technology, Guangxi, Liuzhou, 545006, China


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© Li et al.; Licensee Bentham Open.

open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

* Address correspondence to this author at Shunde Polytechnic, Desheng East Road, Shunde District, Foshan City, Guangdong province, 528300, China; Tel: 13420841579; Fax: 0757-22322669; E-mail: lyjfirst@163.com, 5380901@qq.com


Abstract

The stability problem for a class of stochastic neural networks with Markovian jump parameters and leakage delay is addressed in this study. The sufficient condition to ensure an exponentially stable stochastic neural networks system is presented and proven with Lyapunov functional theory, stochastic stability technique and linear matrix inequality method. The effect of leakage delay on the stability of the neural networks system is discussed and numerical examples are provided to show the correctness and effectiveness of the research results .

Keywords: Markovian jumping, Exponentially stable, Linear matrix inequality (LMI), Neural networks, Time-varying delay, Leakage delay.