Masami Takata

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This paper focuses on a new extension version of double Divide and Conquer (dDC) algorithm to eigen decomposition. Recently, dDC was proposed for singular value decomposition (SVD) of rectangular matrix. The dDC for SVD consists of two parts. One is Divide and Conquer (D&C) for singular value and the other is twisted factorization for singular vector. The(More)
Let a singular value of a bidiagonal matrix be known. Then the corresponding singular vector can be computed through the twisted factorization of a tridiagonal matrix by the discrete Lotka-Volterra with variable step-size (dLVv) transformation. Errors of the singular value then sensitively affect the conditional number of the tridiagonal matrix. In this(More)