A fast SVD for multilevel block Hankel matrices with minimal memory storage

DOI10.1007/s11075-014-9930-0zbMath1322.65052OpenAlexW2038852905MaRDI QIDQ494681

Sanzheng Qiao, Wei Xu, Ling Lü

Publication date: 1 September 2015

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

Full work available at URL: https://doi.org/10.1007/s11075-014-9930-0

zbMATH Keywords

algorithmfast Fourier transformnumerical experimentmatrix-vector multiplicationLanczos processsingular value decomposition (SVD)Cadzow filteringmulti-level block Hankel matrixseismic data processingtwisted factorization method

Mathematics Subject Classification ID

Numerical solutions to overdetermined systems, pseudoinverses (65F20) Seismology (including tsunami modeling), earthquakes (86A15) Toeplitz, Cauchy, and related matrices (15B05)

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Uses Software

• LAPACK95

Cites Work

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• Low rank approximation. Algorithms, implementation, applications
• A Lanczos bidiagonalization algorithm for Hankel matrices
• Extracting qualitative dynamics from experimental data
• Structured low rank approximation
• A fast symmetric SVD algorithm for square Hankel matrices
• LAPACK95 Users' Guide
• Randomized algorithms for the low-rank approximation of matrices
• A twisted factorization method for symmetric SVD of a complex symmetric tridiagonal matrix
• Signal enhancement-a composite property mapping algorithm
• On Computing an Eigenvector of a Tridiagonal Matrix. Part I: Basic Results
• An Introduction to Iterative Toeplitz Solvers