Region Stability and Stabilization of Recurrent Neural Network with Parameter Disturbances

被引：6
作者：
Bao, Gang [1 ]
Peng, Yue [1 ]
Zhou, Xue [1 ]
Gong, Shunqi [1 ]
机构：
[1] China Three Gorges Univ, Hubei Key Lab Cascaded Hydropower Stn Operat & Co, Yichang 443002, Peoples R China
来源：
NEURAL PROCESSING LETTERS | 2020年 / 52卷 / 03期
关键词：
Region stability; Stabilization; Recurrent neural networks; Adaptive control; GLOBAL EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; LAGRANGE STABILITY; ROBUST STABILITY; GENERAL-CLASS; TIME; DELAYS; MULTISTABILITY; INVARIANT; CRITERIA;
D O I：
10.1007/s11063-020-10344-2
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 mainly focuses on global region stability and stabilization analysis for recurrent neural networks with certain or uncertain parameter disturbances. Firstly, it presents global region stability results for recurrent neural networks with certain parameter disturbances by state partition and mathematical analysis methods. Next, it designs one adaptive controller to stabilize network states to the desired region for recurrent neural networks with uncertain parameter disturbances. At last, it gives two numerical examples for verifying obtained results.
引用
收藏
页码：2175 / 2188
页数：14
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