Phase space reconstruction of nonlinear time series based on Kernel method

Shukuan Lin; Jianzhong Qiao; Guoren Wang; Shaomin Zhang; Lijia Zhi

doi:10.1109/WCICA.2006.1713201

Phase space reconstruction of nonlinear time series based on Kernel method

Shukuan Lin^*
, Jianzhong Qiao
, Guoren Wang
, Shaomin Zhang
, Lijia Zhi

^*此作品的通讯作者

Northeastern University China

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

6 引用（Scopus）

摘要

A phase space reconstruction method KPCA-CA was proposed based on Kernel Principal Component Analysis (KPCA) and Correlation Analysis (CA) for nonlinear time series. On the basis of KPCA, the correlation was analyzed between every kernel principal component and output variable, and some kernel principal components were discontinuously chosen according to their correlation degree to form the phase space of nonlinear time series. The method was compared with other methods of phase space reconstruction. The experimental results show that modeling accuracy for nonlinear time series is highest based on the phase space reconstruction method proposed by the paper, proving the efficiency of the method.

源语言	英语
主期刊名	Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
页	4364-4368
页数	5
DOI	https://doi.org/10.1109/WCICA.2006.1713201
出版状态	已出版 - 2006
已对外发布	是
活动	6th World Congress on Intelligent Control and Automation, WCICA 2006 - Dalian, 中国期限: 21 6月 2006 → 23 6月 2006

出版系列

姓名	Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
卷	1

会议

会议	6th World Congress on Intelligent Control and Automation, WCICA 2006
国家/地区	中国
市	Dalian
时期	21/06/06 → 23/06/06

访问文件

10.1109/WCICA.2006.1713201

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链接到 Scopus 的出版物

引用此

Lin, S., Qiao, J., Wang, G., Zhang, S., & Zhi, L. (2006). Phase space reconstruction of nonlinear time series based on Kernel method. 在 Proceedings of the World Congress on Intelligent Control and Automation (WCICA) (页码 4364-4368). 文章 1713201 (Proceedings of the World Congress on Intelligent Control and Automation (WCICA); 卷 1). https://doi.org/10.1109/WCICA.2006.1713201

@inproceedings{06441ede1e1a4d0ca0a8b1cb3fcc034f,

title = "Phase space reconstruction of nonlinear time series based on Kernel method",

abstract = "A phase space reconstruction method KPCA-CA was proposed based on Kernel Principal Component Analysis (KPCA) and Correlation Analysis (CA) for nonlinear time series. On the basis of KPCA, the correlation was analyzed between every kernel principal component and output variable, and some kernel principal components were discontinuously chosen according to their correlation degree to form the phase space of nonlinear time series. The method was compared with other methods of phase space reconstruction. The experimental results show that modeling accuracy for nonlinear time series is highest based on the phase space reconstruction method proposed by the paper, proving the efficiency of the method.",

keywords = "Correlation analysis, Kernel principal component analysis, Nonlinear time series, Phase space reconstruction",

author = "Shukuan Lin and Jianzhong Qiao and Guoren Wang and Shaomin Zhang and Lijia Zhi",

year = "2006",

doi = "10.1109/WCICA.2006.1713201",

language = "English",

isbn = "1424403324",

series = "Proceedings of the World Congress on Intelligent Control and Automation (WCICA)",

pages = "4364--4368",

booktitle = "Proceedings of the World Congress on Intelligent Control and Automation (WCICA)",

note = "6th World Congress on Intelligent Control and Automation, WCICA 2006 ; Conference date: 21-06-2006 Through 23-06-2006",

}

Lin, S, Qiao, J, Wang, G, Zhang, S & Zhi, L 2006, Phase space reconstruction of nonlinear time series based on Kernel method. 在 Proceedings of the World Congress on Intelligent Control and Automation (WCICA)., 1713201, Proceedings of the World Congress on Intelligent Control and Automation (WCICA), 卷 1, 页码 4364-4368, 6th World Congress on Intelligent Control and Automation, WCICA 2006, Dalian, 中国, 21/06/06. https://doi.org/10.1109/WCICA.2006.1713201

Phase space reconstruction of nonlinear time series based on Kernel method. / Lin, Shukuan; Qiao, Jianzhong; Wang, Guoren 等.
Proceedings of the World Congress on Intelligent Control and Automation (WCICA). 2006. 页码 4364-4368 1713201 (Proceedings of the World Congress on Intelligent Control and Automation (WCICA); 卷 1).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Phase space reconstruction of nonlinear time series based on Kernel method

AU - Lin, Shukuan

AU - Qiao, Jianzhong

AU - Wang, Guoren

AU - Zhang, Shaomin

AU - Zhi, Lijia

PY - 2006

Y1 - 2006

N2 - A phase space reconstruction method KPCA-CA was proposed based on Kernel Principal Component Analysis (KPCA) and Correlation Analysis (CA) for nonlinear time series. On the basis of KPCA, the correlation was analyzed between every kernel principal component and output variable, and some kernel principal components were discontinuously chosen according to their correlation degree to form the phase space of nonlinear time series. The method was compared with other methods of phase space reconstruction. The experimental results show that modeling accuracy for nonlinear time series is highest based on the phase space reconstruction method proposed by the paper, proving the efficiency of the method.

AB - A phase space reconstruction method KPCA-CA was proposed based on Kernel Principal Component Analysis (KPCA) and Correlation Analysis (CA) for nonlinear time series. On the basis of KPCA, the correlation was analyzed between every kernel principal component and output variable, and some kernel principal components were discontinuously chosen according to their correlation degree to form the phase space of nonlinear time series. The method was compared with other methods of phase space reconstruction. The experimental results show that modeling accuracy for nonlinear time series is highest based on the phase space reconstruction method proposed by the paper, proving the efficiency of the method.

KW - Correlation analysis

KW - Kernel principal component analysis

KW - Nonlinear time series

KW - Phase space reconstruction

UR - https://www.scopus.com/pages/publications/34047200578

U2 - 10.1109/WCICA.2006.1713201

DO - 10.1109/WCICA.2006.1713201

M3 - Conference contribution

AN - SCOPUS:34047200578

SN - 1424403324

SN - 9781424403325

T3 - Proceedings of the World Congress on Intelligent Control and Automation (WCICA)

SP - 4364

EP - 4368

BT - Proceedings of the World Congress on Intelligent Control and Automation (WCICA)

T2 - 6th World Congress on Intelligent Control and Automation, WCICA 2006

Y2 - 21 June 2006 through 23 June 2006

ER -

Phase space reconstruction of nonlinear time series based on Kernel method

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