Periodic oscillation of memristor-based recurrent neural networks with time-varying delays and leakage delays
International Journal of Intelligent Computing and Cybernetics
ISSN: 1756-378X
Article publication date: 9 July 2018
Issue publication date: 24 July 2018
Abstract
Purpose
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/approach
The differential inequality theory and some novel mathematical analysis techniques are applied.
Findings
A set of sufficient conditions which guarantee the existence and global exponential stability of periodic solution of involved model is derived.
Practical implications
It plays an important role in designing the neural networks.
Originality/value
The 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.
Keywords
Acknowledgements
This work is supported by National Natural Science Foundation of China (No. 61673008) and Project of High-level Innovative Talents of Guizhou Province ([2016]5651) and Major Research Project of The Innovation Group of The Education Department of Guizhou Province ([2017]039), Project of Key Laboratory of Guizhou Province with Financial and Physical Features ([2017]004) and Foundation of Science and Technology of Guizhou Province ([2018]1025 and [2018]1020).
Citation
Xu, C. and Li, P. (2018), "Periodic oscillation of memristor-based recurrent neural networks with time-varying delays and leakage delays", International Journal of Intelligent Computing and Cybernetics, Vol. 11 No. 3, pp. 342-352. https://doi.org/10.1108/IJICC-04-2017-0041
Publisher
:Emerald Publishing Limited
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