Synchronization for delayed memristive BAM neural networks using impulsive control with random nonlinearities

Title
Synchronization for delayed memristive BAM neural networks using impulsive control with random nonlinearities
Author(s)
박주현칼리다스마디야라간R. Sakthivel[R. Sakthivel]
Keywords
TIME-VARYING DELAYS; EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; SYSTEMS; CRITERIA; CIRCUIT; STABILIZATION; PASSIVITY; ELEMENT; DESIGN
Issue Date
201505
Publisher
ELSEVIER SCIENCE INC
Citation
APPLIED MATHEMATICS AND COMPUTATION, v.259, pp.967 - 979
Abstract
In this paper, we formulate and investigate the impulsive synchronization of memristor based bidirectional associative memory (BAM) neural networks with time varying delays. Based on the linear matrix inequality (LMI) approach, the impulsive time dependent results are derived for the exponential stability of the error system, which guarantees the exponential synchronization of the BAM model by means of master-slave synchronization concept. Different from the existing models, an observer (slave system) for the considered BAM neural network in this paper is modeled with time-varying and random impulse moments. Some sufficient conditions are obtained to guarantee the exponential synchronization of the BAM model is derived by using the time-varying Lyapunov function. Simple LMI expressions are proposed to find the feedback controller gains at impulse instants. Finally, a numerical example is presented to illustrate the effectiveness of the theoretical results. (C) 2015 Elsevier Inc. All rights reserved.
URI
http://hdl.handle.net/YU.REPOSITORY/32545http://dx.doi.org/10.1016/j.amc.2015.03.022
ISSN
0096-3003
Appears in Collections:
공과대학 > 전기공학과 > Articles
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