Adaptive Lanczos methods for recursive condition estimation

DOI10.1007/BF02145580zbMath0794.65043MaRDI QIDQ1186619

Gene H. Golub, William R. Ferng, Robert J. Plemmons

Publication date: 28 June 1992

Published in: Numerical Algorithms (Search for Journal in Brave)

zbMATH Keywords

convergencenumerical experimentsLanczos methodcondition numbercovariance matrixrecursive least squaressingular valuessignal processingCholesky factor

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Iterative numerical methods for linear systems (65F10) Numerical computation of matrix norms, conditioning, scaling (65F35) Conditioning of matrices (15A12)

Related Items

Tracking the condition number for RLS in signal processing ⋮ Krylov-subspace methods for the Sylvester equation ⋮ An efficient total least squares algorithm based on a rank-revealing two- sided orthogonal decomposition ⋮ Block RLS using row Householder reflections ⋮ Conference celebrating the 60th birthday of Robert J. Plemmons. Papers from the conference, Winston-Salem, NC, USA, January 1999 ⋮ Dedication to Robert J. Plemmons ⋮ An alternative algorithm for a sliding window ULV decomposition

Uses Software

• Matlab

Cites Work

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