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Novel Parallel Multiple Minor Components Extraction Algorithm by Diagonal Matrix Method

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Abstract

In this letter, we propose a novel multiple minor components (MCs) extraction algorithm by adding a diagonal matrix into the Douglas minor subspace trascking algorithm. Through analyzing all the characteristics of the fixed points, it is proven that the proposed algorithm is stable if and only if the state matrix is composed by the desired MCs. Compared with traditional algorithms, the proposed algorithm has two advantages: (1) The initial conditions can be easily satisfied. (2) The permutation of the estimated MCs is explicitly given in prior. Besides, the norm of the state matrix has stability on the manifold, which illustrates that the proposed algorithm has the virtues of anti-jamming capability. Simulation results are presented to further demonstrate the effectiveness of the proposed algorithm.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant 62106242, Grant 62101579, Grant 62273354 and 61903375, and in part by the Shaanxi Province Natural Science Foundation of China under Grant 2020JM-356.

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Authors and Affiliations

  1. 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang, 050081, China

    Yingbin Gao

  2. The Xi’an Research Institute of High Technology, Xi’an, China

    Xiangyu Kong

  3. College of Weaponry Engineering, Naval University of Engineering, Wuhan, Hubei, 430033, China

    Haidi Dong

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  1. Yingbin Gao
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  2. Xiangyu Kong
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  3. Haidi Dong
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Correspondence to Xiangyu Kong.

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Gao, Y., Kong, X. & Dong, H. Novel Parallel Multiple Minor Components Extraction Algorithm by Diagonal Matrix Method. Neural Process Lett 55, 8947–8956 (2023). https://doi.org/10.1007/s11063-023-11186-4

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  • DOI: https://doi.org/10.1007/s11063-023-11186-4

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