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Delay-dependent dynamical analysis of complex-valued memristive neural networks: Continuous-time and discrete-time cases.

Authors :
Wang, Jinling
Jiang, Haijun
Ma, Tianlong
Hu, Cheng
Source :
Neural Networks. May2018, Vol. 101, p33-46. 14p.
Publication Year :
2018

Abstract

This paper considers the delay-dependent stability of memristive complex-valued neural networks (MCVNNs). A novel linear mapping function is presented to transform the complex-valued system into the real-valued system. Under such mapping function, both continuous-time and discrete-time MCVNNs are analyzed in this paper. Firstly, when activation functions are continuous but not Lipschitz continuous, an extended matrix inequality is proved to ensure the stability of continuous-time MCVNNs. Furthermore, if activation functions are discontinuous, a discontinuous adaptive controller is designed to acquire its stability by applying Lyapunov–Krasovskii functionals. Secondly, compared with techniques in continuous-time MCVNNs, the Halanay-type inequality and comparison principle are firstly used to exploit the dynamical behaviors of discrete-time MCVNNs. Finally, the effectiveness of theoretical results is illustrated through numerical examples. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08936080
Volume :
101
Database :
Academic Search Index
Journal :
Neural Networks
Publication Type :
Academic Journal
Accession number :
128611970
Full Text :
https://doi.org/10.1016/j.neunet.2018.01.015