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Improved synchronization criteria for fractional-order complex-valued neural networks via partial control.

Authors :
Li, Hong-Li
Muhammadhaji, Ahmadjan
Zhang, Long
Jiang, Haijun
Teng, Zhidong
Source :
Advances in Difference Equations; 7/23/2020, Vol. 2020 Issue 1, p1-14, 14p
Publication Year :
2020

Abstract

In this article, without dividing a complex-valued neural network into two real-valued subsystems, the global synchronization of fractional-order complex-valued neural networks (FOCVNNs) is investigated by the Lyapunov direct method rather than the real decomposition method. It is worth mentioning that the partial adaptive control and partial linear feedback control schemes are introduced, by constructing suitable Lyapunov functions, some improved synchronization criteria are derived with the help of fractional differential inequalities and L'Hospital rule as well as some complex analysis techniques. Finally, simulation results are given to demonstrate the validity and feasibility of our theoretical analysis. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16871839
Volume :
2020
Issue :
1
Database :
Complementary Index
Journal :
Advances in Difference Equations
Publication Type :
Academic Journal
Accession number :
144730322
Full Text :
https://doi.org/10.1186/s13662-020-02810-x