A singular value decomposition updating algorithm for subspace tracking thinking dating united states


06-Dec-2019 05:28

An earlier version of this algorithm for a product of two matrices was developed by Heath, Laub, Paige and Ward =-=[9]-=-. In terms of the design of an algorithm, by working in terms of the factors, at each stage of the algo... due to Bojanczyk, Ewerbring, Luk and Van Dooren [3] which is based on Jacobi matrices. The most recent work by Bai and Demmel [7], and Adams, Bojanczyk, Ewerbring, Lu... We discuss a number of novel issues in the interdisciplinary area of numerical linear algebra and control theory. Subject Classifications: AMS(MOS): 65F30; CR: G1.3 1 Introduction The singular value decomposition (SVD) of a matrix is one of the most important tools in numerical linear algebra. Recently, Stewart [52] gave an excellent survey on the early history of the SVD back to the contributions of E. With the development of the Kogbetliantz algorithm for computing the SVD of a product of two matrices by Heath, Laub, Paige and Ward =-=[31]-=- and Hari and Veseli'c [30], Paige proposed a generalization of the Kogbetliantz algorithm to compute the GSVD directly. A number of recent algorithms by Bojanczyk, Golub and Van Dooren; Bojanczyk, Ewerbring and Luk; D.

a singular value decomposition updating algorithm for subspace tracking-65

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These are: sparse matrices, structured matrices, ..." We discuss a number of novel issues in the interdisciplinary area of numerical linear algebra and control theory.The first two were developed independently of each other and have dist ..." In this paper we review the state of affairs in the area of approximation of large-scale systems.