Phase space reconstruction of nonlinear time series based on kernel method

被引：0
|
作者：
Lin, Shukuan [1 ]
Qiao, Jianzhong [1 ]
Wang, Guoren [1 ]
Zhang, Shaomin [1 ]
Zhi, Lijia [1 ]
机构：
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang, Peoples R China
来源：
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年
关键词：
Kernel Principal Component Analysis; Correlation Analysis; phase space reconstruction; nonlinear time series;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
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 even, 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.
引用
收藏
页码：4364 / +
页数：2
相关论文
共 50 条
  • [1] Generic Phase Space Reconstruction Method of Multivariate Time Series
    Kong, Lingshuang
    Yang, Chunhua
    Wang, Yalin
    Gui, Weihua
    [J]. CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS, 2009, : 3752 - 3755
  • [2] Research on the Phase Space Reconstruction Method of Chaotic Time Series
    Ma, Yunfei
    Niu, Peifeng
    Ma, Xiaofei
    [J]. ADVANCED MECHANICAL ENGINEERING, PTS 1 AND 2, 2010, 26-28 : 236 - +
  • [3] Complex network from time series based on phase space reconstruction
    Gao, Zhongke
    Jin, Ningde
    [J]. CHAOS, 2009, 19 (03)
  • [4] Study on Predication of Chaotic Time Series Based on Phase Space Reconstruction
    Liu, Shuyong
    Zhang, Yongxiang
    Zhu, Shijian
    He, Qiwei
    [J]. PROCEEDINGS OF THE 2011 INTERNATIONAL CONFERENCE ON INFORMATICS, CYBERNETICS, AND COMPUTER ENGINEERING (ICCE2011), VOL 3: COMPUTER NETWORKS AND ELECTRONIC ENGINEERING, 2011, 112 : 87 - 97
  • [5] A Density based Method for Multivariate Time Series Clustering in Kernel Feature Space
    Chandrakala, S.
    Sekhar, C. Ch Indra
    [J]. 2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8, 2008, : 1885 - 1890
  • [6] Prediction of multivariate chaotic time series based on optimized phase space reconstruction
    Wang Yijie
    Han Min
    [J]. PROCEEDINGS OF THE 26TH CHINESE CONTROL CONFERENCE, VOL 3, 2007, : 169 - +
  • [7] Phase Space Reconstruction-Based Conceptor Network for Time Series Prediction
    Xu, Zheng
    Zhong, Ling
    Zhang, Anguo
    [J]. IEEE ACCESS, 2019, 7 : 163172 - 163179
  • [8] Chaotic Time Series Prediction Based on Phase Space Reconstruction and LSSVR Model
    Qiao Meiying
    Ma Xiaoping
    Tao Hui
    [J]. 2011 30TH CHINESE CONTROL CONFERENCE (CCC), 2011, : 3243 - 3247
  • [9] Eventuality segments extraction from a time series based on phase space reconstruction
    Wu, Xu
    Dong, Yonggui
    Hou, Zhongjie
    Cheng, Weidong
    [J]. Zhendong yu Chongji/Journal of Vibration and Shock, 2020, 39 (19): : 39 - 47
  • [10] Application of Chaotic Phase Space Reconstruction into Nonlinear Time Series Prediction in Deep Rock Mass
    Kang, Yong
    Li, Xiaohong
    Lu, Yiyu
    Yang, Chunhe
    [J]. FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 5, PROCEEDINGS, 2008, : 593 - +
12345