Boundedness, Mittag-Leffler stability and asymptotical ω-periodicity of fractional-order fuzzy neural networks

被引：66
|
作者：
Wu, Ailong [1 ,2 ,3 ]
Zeng, Zhigang [2 ]
机构：
[1] Hubei Normal Univ, Coll Math & Stat, Huangshi 435002, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Peoples R China
[3] Xi An Jiao Tong Univ, Inst Informat & Syst Sci, Xian 710049, Peoples R China
来源：
NEURAL NETWORKS | 2016年 / 74卷
基金：
中国国家自然科学基金;
关键词：
Fractional-order systems; Fuzzy neural networks; Boundedness; Mittag-Leffler stability; S-asymptotical omega-periodicity; TIME-VARYING DELAYS; GLOBAL EXPONENTIAL STABILITY; MARKOVIAN JUMPING PARAMETERS; REACTION-DIFFUSION; ROBUST STABILITY; SYNCHRONIZATION; CHAOS; IMPULSES; DISCRETE; EXISTENCE;
D O I：
10.1016/j.neunet.2015.11.003
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We show that the omega-periodic fractional-order fuzzy neural networks cannot generate non-constant omega-periodic signals. In addition, several sufficient conditions are obtained to ascertain the boundedness and global Mittag-Leffler stability of fractional-order fuzzy neural networks. Furthermore, S-asymptotical omega-periodicity and global asymptotical omega-periodicity of fractional-order fuzzy neural networks is also characterized. The obtained criteria improve and extend the existing related results. To illustrate and compare the theoretical criteria, some numerical examples with simulation results are discussed in detail. Crown Copyright (C) 2015 Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：73 / 84
页数：12
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