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  • 65F20  (1)
  • Mathematics Subject Classification (1991):65F15  (1)
  • downdating  (1)
  • subspaces  (1)
Materialart
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  • 1
    Digitale Medien
    Digitale Medien
    Springer
    BIT 36 (1996), S. 14-40 
    ISSN: 1572-9125
    Schlagwort(e): Orthogonal decomposition ; downdating ; error analysis ; subspaces
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Mathematik
    Notizen: Abstract An alternative to performing the singular value decomposition is to factor a matrixA into $$A = U\left( {\begin{array}{*{20}c} C \\ 0 \\ \end{array} } \right)V^T $$ , whereU andV are orthogonal matrices andC is a lower triangular matrix which indicates a separation between two subspaces by the size of its columns. These subspaces are denoted byV = (V 1,V 2), where the columns ofC are partitioned conformally intoC = (C 1,C 2) with ‖C 2 ‖ F ≤ ε. Here ε is some tolerance. In recent years, this has been called the ULV decomposition (ULVD). If the matrixA results from statistical observations, it is often desired to remove old observations, thus deleting a row fromA and its ULVD. In matrix terms, this is called a downdate. A downdating algorithm is proposed that preserves the structure in the downdated matrix $$\bar C$$ to the extent possible. Strong stability results are proven for these algorithms based upon a new perturbation theory.
    Materialart: Digitale Medien
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 2
    Digitale Medien
    Digitale Medien
    Springer
    BIT 31 (1991), S. 375-379 
    ISSN: 1572-9125
    Schlagwort(e): 65F20 ; 65F25
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Mathematik
    Notizen: Abstract We present a numerical algorithm for computing the implicit QR factorization of a product of three matrices, and we illustrate the technique by applying it to the generalized total least squares and the restricted total least squares problems. We also demonstrate how to take advantage of the block structures of the underlying matrices in order to reduce the computational work.
    Materialart: Digitale Medien
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 3
    Digitale Medien
    Digitale Medien
    Springer
    Numerische Mathematik 72 (1996), S. 391-417 
    ISSN: 0945-3245
    Schlagwort(e): Mathematics Subject Classification (1991):65F15
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Mathematik
    Notizen: Summary. We present a numerical algorithm for computing a few extreme generalized singular values and corresponding vectors of a sparse or structured matrix pair $\{A,B\}$ . The algorithm is based on the CS decomposition and the Lanczos bidiagonalization process. At each iteration step of the Lanczos process, the solution to a linear least squares problem with $(A^{\rm T},B^{\rm T})^{\rm T}$ as the coefficient matrix is approximately computed, and this consists the only interface of the algorithm with the matrix pair $\{A,B\}$ . Numerical results are also given to demonstrate the feasibility and efficiency of the algorithm.
    Materialart: Digitale Medien
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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