IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v175y2023ip1s0960077923008469.html
   My bibliography  Save this article

Unequal-step multiscale integrated mapping dispersion Lempel-Ziv complexity: A novel complexity metric for signal analysis

Author

Listed:
  • Li, Yuxing
  • Wu, Junxian
  • Yi, Yingmin
  • Gu, Yunpeng

Abstract

Dispersion Lempel-Ziv complexity (DLZC), as a more effective complexity metric proposed in recent years, can effectively quantify the dynamic change of signal. However, DLZC still has shortcomings of insufficient applicability and lack of scale information. To surmount these drawbacks, we fully utilize the advantages of multiple mapping methods and integrate these mapping methods into DLZC, thus the integrated mapping DLZC (IMDLZC) is proposed, which has higher separability and applicability. Moreover, we developed a coarse-grained method called unequal step multi scale analysis, which solves the problem that the defects of subsequences decrease sharply with the increase of scale in existing coarse-grained methods. Then a new complexity metric for signal analysis called unequal-step multiscale IMDLZC (UM-IMDLZC) is proposed by coupling unequal-step multiscale analysis and IMDLZC. The experimental results of three kinds of synthetic signals show that UM-IMDLZC is more sensitive to the dynamic changes of signals and has the more excellent robustness; moreover, compared with other four complexity metrics, the proposed UM-IMDLZC has the best classification effect for different types of realistic signals.

Suggested Citation

  • Li, Yuxing & Wu, Junxian & Yi, Yingmin & Gu, Yunpeng, 2023. "Unequal-step multiscale integrated mapping dispersion Lempel-Ziv complexity: A novel complexity metric for signal analysis," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    • Handle: RePEc:eee:chsofr:v:175:y:2023:i:p1:s0960077923008469
    DOI: 10.1016/j.chaos.2023.113945
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077923008469
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2023.113945?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mao, Xuegeng & Shang, Pengjian & Xu, Meng & Peng, Chung-Kang, 2020. "Measuring time series based on multiscale dispersion Lempel–Ziv complexity and dispersion entropy plane," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    2. Wang, Zhuo & Shang, Pengjian, 2021. "Generalized entropy plane based on multiscale weighted multivariate dispersion entropy for financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    3. Li, Yuxing & Geng, Bo & Jiao, Shangbin, 2022. "Dispersion entropy-based Lempel-Ziv complexity: A new metric for signal analysis," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wan, Li & Ling, Guang & Guan, Zhi-Hong & Fan, Qingju & Tong, Yu-Han, 2022. "Fractional multiscale phase permutation entropy for quantifying the complexity of nonlinear time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    2. Gu, Danlei & Lin, Aijing & Lin, Guancen, 2022. "Sleep and cardiac signal processing using improved multivariate partial compensated transfer entropy based on non-uniform embedding," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    3. Li, Sange & Shang, Pengjian, 2022. "A new complexity measure: Modified discrete generalized past entropy based on grain exponent," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    4. Li, Yuxing & Geng, Bo & Jiao, Shangbin, 2022. "Dispersion entropy-based Lempel-Ziv complexity: A new metric for signal analysis," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    5. Fabila-Carrasco, John Stewart & Tan, Chao & Escudero, Javier, 2023. "Dispersion entropy for graph signals," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:175:y:2023:i:p1:s0960077923008469. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.