Synchronization for delayed memristive BAM neural networks using impulsive control with random nonlinearities
作者： K. Mathiyalagan , Ju H. Park , R. Sakthivel
DOI: 10.1016/J.AMC.2015.03.022
关键词: Observer (special relativity) 、 Memristor 、 Computer science 、 Impulse (physics) 、 Artificial neural network 、 Exponential stability 、 Linear matrix inequality 、 Lyapunov function 、 Bidirectional associative memory 、 Control theory
摘要: 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 linear matrix inequality (LMI) approach, dependent results are derived for exponential stability error system, which guarantees BAM model by means master-slave concept. Different from existing models, an observer (slave system) considered network in paper is modeled time-varying random impulse moments. Some sufficient conditions obtained to guarantee using Lyapunov function. Simple LMI expressions proposed find feedback controller gains at instants. Finally, a numerical example presented illustrate effectiveness theoretical results.
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