Title: Robust stability analysis for uncertain stochastic neural networks with mixed time-varying delays

Authors: Yonggang Chen, Tiheng Qin

Addresses: Department of Mathematics, Henan Institute of Science and Technology, Xinxiang 453003, PR China. ' Department of Basic Courses, Henan Mechanical and Electrical Engineering College, Xinxiang 453002, PR China

Abstract: In this paper, the robust exponential stability analysis is investigated for a class of uncertain stochastic neural networks with discrete and distributed time-varying delays. Based on the Lyapunov functional method, and by applying the novel technique for estimating the upper bound of infinitesimal operator L of the stochastic process, the less conservative exponential stability criteria are derived in terms of Linear Matrix Inequalities (LMIs). Finally, two numerical examples are presented to show the less conservativeness of the obtained results.

Keywords: exponential stability; stochastic neural networks; time-varying delays; LMIs; linear matrix inequalities.

DOI: 10.1504/IJSCC.2010.035423

International Journal of Systems, Control and Communications, 2010 Vol.2 No.4, pp.364 - 378

Published online: 30 Sep 2010 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article