Journal of Optoelectronics · Laser, Volume. 35, Issue 10, 1058(2024)

Block robust tensor principal component analysis based on area projection

ZHANG Xiaomin1, ZHANG Chao2, SHI Leyan1, and WANG Xiaofeng1,3
Author Affiliations
  • 1Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, Tianjin University of Technology, Tianjin 300384, China
  • 2BingooRobot (Tianjin) Co., Ltd, Tianjin 300401, China
  • 3National Demonstration Center for Experimental Mechanical and Electrical Engineering Education, Tianjin University of Technology, Tianjin 300384, China
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    References(16)

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    [9] [9] WANG R, NIE F P, YANG X J, et al. Robust 2DPCA with non-greedy L1-norm maximization for image analysis[J]. IEEE Transactions on Cybernetics, 2015, 45(5): 1108-1112.

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    [16] [16] TANG G Y, LU G F, WANG Z Q, et al. Robust tensor prin-cipal component analysis by LP-norm for image analysis[C]//2016 2nd IEEE International Conference on Computer and Communications, October 14-17, 2016, Chengdu, China. New York: IEEE, 2016: 568-573.

    [17] [17] GE W M, LI J X, WANG X F. Robust tensor principal component analysis based on F-norm[C]//Proceedings of 2020 IEEE International Conference on Mechatronics and Automation, October 13-16, 2020, Beijing, China. New York: IEEE, 2020: 1077-1082.

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    ZHANG Xiaomin, ZHANG Chao, SHI Leyan, WANG Xiaofeng. Block robust tensor principal component analysis based on area projection[J]. Journal of Optoelectronics · Laser, 2024, 35(10): 1058

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    Paper Information

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    Received: Aug. 2, 2023

    Accepted: Dec. 31, 2024

    Published Online: Dec. 31, 2024

    The Author Email:

    DOI:10.16136/j.joel.2024.10.0416

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