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The Singular Value Decomposition over Completed Idempotent Semifields

Author

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  • Francisco J. Valverde-Albacete

    (Department of Signal Theory and Communications, Universidad Carlos III de Madrid, 28911 Leganés, Spain
    These authors contributed equally to this work.)

  • Carmen Peláez-Moreno

    (Department of Signal Theory and Communications, Universidad Carlos III de Madrid, 28911 Leganés, Spain
    These authors contributed equally to this work.)

Abstract

In this paper, we provide a basic technique for Lattice Computing: an analogue of the Singular Value Decomposition for rectangular matrices over complete idempotent semifields (i-SVD). These algebras are already complete lattices and many of their instances—the complete schedule algebra or completed max-plus semifield, the tropical algebra, and the max-times algebra—are useful in a range of applications, e.g., morphological processing. We further the task of eliciting the relation between i-SVD and the extension of Formal Concept Analysis to complete idempotent semifields (K-FCA) started in a prior work. We find out that for a matrix with entries considered in a complete idempotent semifield, the Galois connection at the heart of K-FCA provides two basis of left- and right-singular vectors to choose from, for reconstructing the matrix. These are join-dense or meet-dense sets of object or attribute concepts of the concept lattice created by the connection, and they are almost surely not pairwise orthogonal. We conclude with an attempt analogue of the fundamental theorem of linear algebra that gathers all results and discuss it in the wider setting of matrix factorization.

Suggested Citation

  • Francisco J. Valverde-Albacete & Carmen Peláez-Moreno, 2020. "The Singular Value Decomposition over Completed Idempotent Semifields," Mathematics, MDPI, vol. 8(9), pages 1-39, September.
  • Handle: RePEc:gam:jmathe:v:8:y:2020:i:9:p:1577-:d:412746
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    References listed on IDEAS

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    1. Scott Deerwester & Susan T. Dumais & George W. Furnas & Thomas K. Landauer & Richard Harshman, 1990. "Indexing by latent semantic analysis," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 391-407, September.
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    Cited by:

    1. Mariya Kornilova & Vladislav Kovalnogov & Ruslan Fedorov & Mansur Zamaleev & Vasilios N. Katsikis & Spyridon D. Mourtas & Theodore E. Simos, 2022. "Zeroing Neural Network for Pseudoinversion of an Arbitrary Time-Varying Matrix Based on Singular Value Decomposition," Mathematics, MDPI, vol. 10(8), pages 1-12, April.
    2. Vassilis G. Kaburlasos, 2022. "Lattice Computing: A Mathematical Modelling Paradigm for Cyber-Physical System Applications," Mathematics, MDPI, vol. 10(2), pages 1-3, January.

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