Pseudo Almost Periodic Solutions for High-Order Hopfield Neural Networks with Time-Varying Leakage Delays

被引：22
作者：
Xu, Changjin [1 ]
Li, Peiluan [2 ]
机构：
[1] Guizhou Univ Finance & Econ, Guizhou Key Lab Econ Syst Simulat, Guiyang 550004, Guizhou, Peoples R China
[2] Henan Univ Sci & Technol, Sch Math & Stat, Luoyang 471023, Peoples R China
来源：
NEURAL PROCESSING LETTERS | 2017年 / 46卷 / 01期
关键词：
High-order Hopfield neural networks; Pseudo almost periodic solution; Exponential stability; Leakage delay; Lyapunov functional; GLOBAL EXPONENTIAL STABILITY; ANTIPERIODIC SOLUTIONS; DISTRIBUTED DELAYS; EXISTENCE; MODEL;
D O I：
10.1007/s11063-016-9573-3
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, high-order Hopfield neural networks with time-varying leakage delays are investigated. By applying Lyapunov functional method and differential inequality techniques, a set of sufficient conditions are obtained for the existence and exponential stability of pseudo almost periodic solutions of the model. Some simulations are carried out to support the theoretical findings. Our results improve and generalize those of the previous studies.
引用
收藏
页码：41 / 58
页数：18
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