Stability Analysis for Stochastic Markovian Jumping Neural Networks with Leakage Delay
Yajun Li1, *, Xisheng Dai2, Wenping Xiao1, Like Jiao1
Identifiers and Pagination:Year: 2017
First Page: 1
Last Page: 13
Publisher Id: TOEEJ-11-1
Article History:Received Date: 15/01/2016
Revision Received Date: 31/08/2016
Acceptance Date: 01/09/2016
Electronic publication date: 25/01/2017
Collection year: 2016
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.
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 .