Adaptive estimation for delayed neural networks with Markovian jumping parameters

被引：6

作者：

Tong, Dongbing ^{[1
,2
,3
]}

Zhou, Wuneng ^{[2
]}

Wang, Han ^{[3
]}

Zhou, Jun ^{[2
]}

Zhou, Xianghui ^{[4
]}

Xu, Yuhua ^{[5
]}

机构：

[1] Shanghai Univ Engn Sci, Sch Elect & Elect Engn, Shanghai 201620, Peoples R China

[2] Donghua Univ, Coll Informat Sci & Technol, Shanghai 201620, Peoples R China

[3] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore

[4] Yangtze Univ, Freshman Educ Dept, Jing Zhou 434023, Peoples R China

[5] Nanjing Audit Univ, Sch Finance, Nanjing 211815, Jiangsu, Peoples R China

来源：

OPTIK | 2015年 / 126卷 / 21期

基金：

上海市自然科学基金;

关键词：

Neural networks; Adaptive estimation; Markovian jumping parameters; Time delays; COMPLEX DYNAMICAL NETWORKS; STATE ESTIMATION; SYNCHRONIZATION;

D O I：

10.1016/j.ijleo.2015.07.055

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

In this letter, the adaptive estimation problem of the neuron states is studied for delayed neural networks with Markovian jumping parameters. Through employing a new nonnegative function and the M-matrix method, some sufficient conditions are derived to ensure the almost sure asymptotical stability for the dynamics of estimator error. Several suitable parameters update laws are found by the adaptive feedback control technique. Finally, a simulation example is provided to illustrate the effectiveness of the proposed adaptive estimation method. (C) 2015 Elsevier GmbH. All rights reserved.

引用

页码：2960 / 2964

页数：5

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