Asymptotical Stability of Riemann-Liouville Fractional-Order Neutral-Type Delayed Projective Neural Networks

被引：18
|
作者：
Li, Jin-dong [1 ,2 ]
Wu, Zeng-bao [3 ]
Huang, Nan-jing [2 ]
机构：
[1] Chengdu Univ Technol, Coll Management Sci, Chengdu 610059, Sichuan, Peoples R China
[2] Sichuan Univ, Dept Math, Chengdu 610064, Sichuan, Peoples R China
[3] Luoyang Normal Univ, Dept Math, Luoyang 471934, Henan, Peoples R China
来源：
NEURAL PROCESSING LETTERS | 2019年 / 50卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Fractional-order projective neural network; LMI technique; Neutral-type delayed projective neural network; Equilibrium point; Asymptotical stability; PERIODIC-SOLUTION; SINGULAR SYSTEMS; EXISTENCE;
D O I：
10.1007/s11063-019-10050-8
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, a new class of Riemann-Liouville fractional-order neutral-type delayed projective neural networks are introduced and studied. By utilizing the linear matrix inequality technique, some sufficient conditions to ensure the asymptotical stability of the equilibrium point of the addressed projective neural networks are presented. Finally, some numerical examples are given to illustrate the validity and feasibility of the main results.
引用
收藏
页码：565 / 579
页数：15
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