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The generalization negation of probability distribution and its application in target recognition based on sensor fusion

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  • Xiaozhuan Gao
  • Yong Deng

Abstract

Target recognition in uncertain environments is a hot issue. Fusion rules are used to combine the sensor reports from different sources. In this situation, obtaining more information to make correct decision is an essential issue. Probability distribution is one of the most used methods to represent uncertainty information. In addition, the negation of probability distribution provides a new view to represent the uncertainty information. In this article, the existing negation of probability distribution is extended with Tsallis entropy. The main reason is that different systems have different parameter q . Some numerical examples are used to demonstrate the efficiency of the proposed method. Besides, the article also discusses the application of negation in target recognition based on sensor fusion to further demonstrate the importance of negation.

Suggested Citation

  • Xiaozhuan Gao & Yong Deng, 2019. "The generalization negation of probability distribution and its application in target recognition based on sensor fusion," International Journal of Distributed Sensor Networks, , vol. 15(5), pages 15501477198, May.
    • Handle: RePEc:sae:intdis:v:15:y:2019:i:5:p:1550147719849381
    DOI: 10.1177/1550147719849381
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Ingo Klein, 2022. "Some Technical Remarks on Negations of Discrete Probability Distributions and Their Information Loss," Mathematics, MDPI, vol. 10(20), pages 1-26, October.
    2. Priya Tanwar & Amit Srivastava, 2023. "Generalization of negation of a probability distribution," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 447-454, March.
    3. Liguo Fei & Jun Xia & Yuqiang Feng & Luning Liu, 2019. "A novel method to determine basic probability assignment in Dempster–Shafer theory and its application in multi-sensor information fusion," International Journal of Distributed Sensor Networks, , vol. 15(7), pages 15501477198, July.
    4. Tanwar, Priya & Srivastava, Amit, 2023. "Negation and redistribution with a preference — An information theoretic analysis," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).

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