Adaptive Synchronization of Fractional-Order Output-Coupling Neural Networks via Quantized Output Control

被引：129

作者：

Bao, Haibo ^{[1
]}

Park, Ju H. ^{[2
]}

Cao, Jinde ^{[3
]}

机构：

[1] Southwest Univ, Sch Math & Stat, Chongqing 400715, Peoples R China

[2] Yeungnam Univ, Dept Elect Engn, Nonlinear Dynam Grp, Kyongsan 38541, South Korea

[3] Southeast Univ, Sch Math, Nanjing 210096, Peoples R China

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS | 2021年 / 32卷 / 07期

基金：

新加坡国家研究基金会; 中国国家自然科学基金;

关键词：

Couplings; Synchronization; Biological neural networks; Neurons; Linear matrix inequalities; Complex networks; Symmetric matrices; Fractional order; neural networks; output coupling; quantized control; synchronization; FINITE-TIME SYNCHRONIZATION; GLOBAL SYNCHRONIZATION; PROJECTIVE SYNCHRONIZATION; STABILITY; SYSTEMS;

D O I：

10.1109/TNNLS.2020.3013619

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This article focuses on the adaptive synchronization for a class of fractional-order coupled neural networks (FCNNs) with output coupling. The model is new for output coupling item in the FCNNs that treat FCNNs with state coupling as its particular case. Novel adaptive output controllers with logarithm quantization are designed to cope with the stability of the fractional-order error systems for the first attempt, which is also an effective way to synchronize fractional-order complex networks. Based on fractional-order Lyapunov functionals and linear matrix inequalities (LMIs) method, sufficient conditions rather than algebraic conditions are built to realize the synchronization of FCNNs with output coupling. A numerical simulation is put forward to substantiate the applicability of our results.

引用

页码：3230 / 3239

页数：10

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