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Periodic oscillation of memristor-based recurrent neural networks with time-varying delays and leakage delays

Periodic oscillation of memristor-based recurrent neural networks with time-varying delays and... The purpose of this paper is to investigate the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.Design/methodology/approachThe differential inequality theory and some novel mathematical analysis techniques are applied.FindingsA set of sufficient conditions which guarantee the existence and global exponential stability of periodic solution of involved model is derived.Practical implicationsIt plays an important role in designing the neural networks.Originality/valueThe obtained results of this paper are new and complement some previous studies. The innovation of this paper concludes two aspects: the analysis on the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays is first proposed; and it is first time to establish the sufficient criterion which ensures the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Intelligent Computing and Cybernetics Emerald Publishing

Periodic oscillation of memristor-based recurrent neural networks with time-varying delays and leakage delays

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1756-378X
DOI
10.1108/ijicc-04-2017-0041
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to investigate the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.Design/methodology/approachThe differential inequality theory and some novel mathematical analysis techniques are applied.FindingsA set of sufficient conditions which guarantee the existence and global exponential stability of periodic solution of involved model is derived.Practical implicationsIt plays an important role in designing the neural networks.Originality/valueThe obtained results of this paper are new and complement some previous studies. The innovation of this paper concludes two aspects: the analysis on the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays is first proposed; and it is first time to establish the sufficient criterion which ensures the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.

Journal

International Journal of Intelligent Computing and CyberneticsEmerald Publishing

Published: Jul 24, 2018

Keywords: Time-varying delay; Leakage delay; Global exponential stability; Memristor-based recurrent neural networks

References