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Deng–Fisher information measure and its extensions: Application to Conway’s Game of Life

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  • Kharazmi, Omid
  • Contreras-Reyes, Javier E.

Abstract

The purpose of this work is to introduce Deng–Fisher information (DFI), Deng–Fisher information distance (DFID) and Jensen–Deng–Fisher (JDF) information distance measures based on the basic probability assignment concept. We also present results associated with these proposed information measures and examine DFI and DFID measures for escort of basic probability assignment functions. For illustrative purpose, we examined Conway’s Game of Life cellular automaton and present numerical results in terms of the proposed information measures. Results indicate that JDF information distance measures living cell population dynamics along time.

Suggested Citation

  • Kharazmi, Omid & Contreras-Reyes, Javier E., 2023. "Deng–Fisher information measure and its extensions: Application to Conway’s Game of Life," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    • Handle: RePEc:eee:chsofr:v:174:y:2023:i:c:s0960077923007725
    DOI: 10.1016/j.chaos.2023.113871
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    References listed on IDEAS

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    1. Cui, Huizi & Zhou, Lingge & Li, Yan & Kang, Bingyi, 2022. "Belief entropy-of-entropy and its application in the cardiac interbeat interval time series analysis," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    2. Telesca, Luciano & Lovallo, Michele & Hsu, Han-Lun & Chen, Chien-Chih, 2011. "Analysis of dynamics in magnetotelluric data by using the Fisher–Shannon method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(7), pages 1350-1355.
    3. Xue, Yige & Deng, Yong, 2022. "A decomposable Deng entropy," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    4. Zhou, Qianli & Deng, Yong, 2023. "Generating Sierpinski gasket from matrix calculus in Dempster–Shafer theory," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    5. Deyun Zhou & Yongchuan Tang & Wen Jiang, 2017. "A modified belief entropy in Dempster-Shafer framework," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-17, May.
    6. Contreras-Reyes, Javier E., 2021. "Lerch distribution based on maximum nonsymmetric entropy principle: Application to Conway’s game of life cellular automaton," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
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    Cited by:

    1. Zhao, Tong & Li, Zhen & Deng, Yong, 2024. "Linearity in Deng entropy," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    2. Contreras-Reyes, Javier E. & Kharazmi, Omid, 2023. "Belief Fisher–Shannon information plane: Properties, extensions, and applications to time series analysis," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).

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