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Stochastic synchronization of coupled neural networks with intermittent control

Authors
Journal
Physics Letters A
0375-9601
Publisher
Elsevier
Publication Date
Volume
373
Issue
36
Identifiers
DOI: 10.1016/j.physleta.2009.07.013
Keywords
  • Nonlinear Science
Disciplines
  • Computer Science
  • Mathematics

Abstract

Abstract In this Letter, we study the exponential stochastic synchronization problem for coupled neural networks with stochastic noise perturbations. Based on Lyapunov stability theory, inequality techniques, the properties of Weiner process, and adding different intermittent controllers, several sufficient conditions are obtained to ensure exponential stochastic synchronization of coupled neural networks with or without coupling delays under stochastic perturbations. These stochastic synchronization criteria are expressed in terms of several lower-dimensional linear matrix inequalities (LMIs) and can be easily verified. Moreover, the results of this Letter are applicable to both directed and undirected weighted networks. A numerical example and its simulations are offered to show the effectiveness of our new results.

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