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Finite-time synchronization and [formula omitted] synchronization of coupled complex-valued memristive neural networks with and without parameter uncertainty.

Authors :
Wu, Fang
Huang, Yanli
Source :
Neurocomputing. Jan2022, Vol. 469, p163-179. 17p.
Publication Year :
2022

Abstract

In this paper, finite-time synchronization and H ∞ synchronization of coupled complex-valued memristive neural networks (CCVMNNs) with or without parameter uncertainty are analyzed. First, a finite-time synchronization (FTS) condition is presented for CCVMNNs by means of deploying Lyapunov stability theory and developing suitable controllers. Then, we utilize the similar method to derive a criterion of robust finite-time synchronization (RFTS) for the proposed CCVMNNs with uncertain parameter. Furthermore, we establish some criteria for the sake of ensuring that the considered network can reach finite-time H ∞ synchronization and robust finite-time H ∞ synchronization. At last, two numerical examples with simulations demonstrate the validity of the acquired results. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09252312
Volume :
469
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
153825650
Full Text :
https://doi.org/10.1016/j.neucom.2021.10.067