4.7 Article

Matrix measure strategies for stability and synchronization of inertial BAM neural network with time delays

Journal

NEURAL NETWORKS
Volume 53, Issue -, Pages 165-172

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2014.02.003

Keywords

Global exponential stability; Global synchronization; Matrix measure; Inertial BAM neural network; Time-varying delays

Funding

  1. National Natural Science Foundation of China [61272530, 11072059]
  2. Natural Science Foundation of Jiangsu Province of China [BK2012741]
  3. Specialized Research Fund for the Doctoral Program of Higher Education [20110092110017, 20130092110017]

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A single inertial BAM neural network with time-varying delays and external inputs is concerned in this paper. First, by choosing suitable variable substitution, the original system can be transformed into first-order differential equations. Then, we present several sufficient conditions for the global exponential stability of the equilibrium by using matrix measure and Halanay inequality, these criteria are simple in form and easy to verify in practice. Furthermore, when employing an error-feedback control term to the response neural network, parallel criteria regarding to the exponential synchronization of the drive-response neural network are also generated. Finally, some examples are given to illustrate our theoretical results. (C) 2014 Elsevier Ltd. All rights reserved.

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