• DocumentCode
    1554055
  • Title

    SVD compression, unitary transforms, and computational complexity

  • Author

    Knockaert, Luc ; De Backer, Bernard ; De Zutter, Daniël

  • Author_Institution
    INTEC, Ghent, Belgium
  • Volume
    47
  • Issue
    10
  • fYear
    1999
  • fDate
    10/1/1999 12:00:00 AM
  • Firstpage
    2724
  • Lastpage
    2729
  • Abstract
    The search for fast unitary transforms and the need for data compression in linear systems are complementary issues. Compression requires the definition of a threshold dependent on the condition number, which is invariant over the unitary group. With respect to this threshold, it is shown that the SVD is the optimal tool. Considerations in connection with the Kronecker product and direct sum of unitary matrices show that the computational complexity of unitary transforms is entropy-like in nature, thereby indicating that the O(n log n) complexity unitary transforms are dense over the unitary group
  • Keywords
    computational complexity; data compression; linear systems; singular value decomposition; transforms; Kronecker product; SVD compression; computational complexity; condition number; data compression; linear systems; threshold; unitary matrices; unitary transforms; Complexity theory; Computational complexity; Data compression; Entropy; Helium; Linear systems; Matrix decomposition; Signal processing algorithms; Singular value decomposition; Working environment noise;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.790654
  • Filename
    790654