Adaptive synchronization of fractional-order complex-valued coupled neural networks via direct error method

被引：20

作者：

Zheng, Bibo ^{[1
]}

Wang, Zhanshan ^{[1
]}

机构：

[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China

来源：

NEUROCOMPUTING | 2022年 / 486卷

基金：

中国国家自然科学基金;

关键词：

Coupled neural network; Complex-valued; Synchronization; Fractional-order; Adaptive law; VARIABLE DYNAMICAL NETWORKS; IMPULSIVE SYNCHRONIZATION; NEUTRAL DELAYS; FINITE-TIME; SYSTEMS;

D O I：

10.1016/j.neucom.2021.11.015

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, without dividing the fractional-order complex-valued coupled neural networks (FCVCNNs) into two real-valued systems, the problem of synchronization is investigated for FCVCNNs with time varying coupling strength. To achieve synchronization, by updating coupling strength, two feasible adaptive protocols are designed, 1) a fractional-order adaptive strategy depending on global information; 2) a fractional-order adaptive law relying on the local information based on the connected dominating set theory. Additionally, instead of making the weighted average technique or the solution of the isolated node equation as synchronization reference value, direct error method is adopted to realize synchronization, which offers a flexible way in analysis of FCVCNNs. At last, a numerical simulation is provided to illustrate the validity of theoretical results.(c) 2021 Elsevier B.V. All rights reserved.

引用

页码：114 / 122

页数：9

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