Global Exponential Stability of Hybrid Non-autonomous Neural Networks with Markovian Switching

被引：4
|
作者：
Zhao, Chenhui [1 ]
Guo, Donghui [1 ]
机构：
[1] Xiamen Univ, Sch Elect Sci & Engn, Dept Elect Engn, Xiamen 361005, Peoples R China
来源：
NEURAL PROCESSING LETTERS | 2020年 / 52卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Global exponential stability; Hybrid non-autonomous neural networks (HNNNs); Pulse delay; Markovian switching; Halanay inequality; TIME-VARYING DELAYS; SYNCHRONIZATION; PARAMETERS;
D O I：
10.1007/s11063-020-10262-3
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper discusses the global exponential stability for a class of hybrid non-autonomous neural networks (HNNNs) with Markovian switching, which includes the factors of time delays and impulse disturbance. A novel Halanay inequality with cross terms is established by using stochastic analysis technique. Some sufficiency criteria for the global exponential stability of the HNNNs with Markovian switching are derived by the Halanay inequality and some mathematical analysis methods. The results obtained have better fault tolerance and redundancy under certain accuracy than the existing results in the literature. Finally, numerical experiments are provided to illustrate our theoretical results.
引用
收藏
页码：525 / 543
页数：19
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