An incremental modular echo state network - 文章详情页

作者：

Li, F.-J. (Li, F.-J..) | Qiao, J.-F. (Qiao, J.-F..) (学者：乔俊飞)

收录：

Scopus PKU CSCD

摘要：

An　incremental　modular　echo　state　network(IM-ESN)　is　proposed　to　solve　the　multiple　superimposed　oscillator(MSO)　problem,　which　is　difficult　to　be　solved　by　conventional　ESNs.　The　reservoir　of　IM-ESN　is　made　up　of　sub-reservoirs　which　are　mutually　independent.　The　weight　matrices　of　sub-reservoirs　are　designed　via　the　singular　value　decomposition(SVD)　method.　Based　on　the　block　diagonal　matrix　theory,　the　generated　sub-reservoirs　are　added　to　the　existing　network　one　by　one.　During　the　growth　of　the　network,　IM-ESN　can　guarantee　the　echo　state　property　without　posterior　scaling　of　the　weights.　The　experiment　results　on　the　MSO　problem　show　that　the　IM-ESN　can　determine　its　network　complexity　to　match　the　given　applications　automatically,　with　better　prediction　performance　and　robustness.　©　2016,　Editorial　Office　of　Control　and　Decision.　All　right　reserved.

关键词：

Echo state network; MSO problem; Prediction; Reservoir; Singular value

作者机构：

[ 1 ] [Li, F.-J.]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [Li, F.-J.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China
[ 3 ] [Li, F.-J.]School of Mathematical Science, University of Ji'nan, Ji'nan, 250022, China
[ 4 ] [Qiao, J.-F.]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 5 ] [Qiao, J.-F.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China

通讯作者信息：

[Li, F.-J.]College of Electronic Information and Control Engineering, Beijing University of TechnologyChina

电子邮件地址：

ss_lifj@ujn.edu.cn

查看成果更多字段

来源：

Control and Decision

ISSN： 1001-0920

年份： 2016

期： 8

卷： 31

页码： 1481-1486

被引次数：

WoS核心集被引频次： 0

近30日浏览量： 1

归属院系：

信息学部

全文获取

DOI 图书馆发现搜索百度学术搜索 SCOPUS

成果类型
所属机构

所有年份指定年份从至