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Bidiagonalization

Known as: Bi-diagonalization 
Bidiagonalization is one of unitary (orthogonal) matrix decompositions such that U* A V = B, where U and V are unitary (orthogonal) matrices… 
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Related topics

Related topics

7 relations
Bidiagonal matrixCharacteristic polynomialLanczos algorithmList of numerical analysis topics

Broader (1)

Numerical linear algebra

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
A fast algorithm for regularized focused 3-D inversion of gravity data using the randomized SVD
A fast algorithm for solving the under-determined 3-D linear gravity inverse problem based on the randomized singular value… 
2015
2015
Reduced-complexity SVD with adjustable accuracy for precoding in large-scale MIMO systems
Singular value decomposition (SVD) plays an important role for MIMO precoding. To reduce the complexity of precoding based on SVD… 
2014
2014
A Low Complexity Geometric Mean Decomposition Computing Scheme and Its High Throughput VLSI Implementation
Geometric Mean Decomposition (GMD) is considered an efficient precoding scheme in joint MIMO transceiver designs capable of… 
Review
2013
Review
2013
A Constant Throughput Geometric Mean Decomposition Scheme Design for Wireless MIMO Precoding
The geometric mean decomposition (GMD) algorithm is a popular approach in developing a precoding scheme for joint multiple-input… 
2013
2013
GENERALIZED GOLUB–KAHAN BIDIAGONALIZATION AND STOPPING CRITERIA∗
The Golub–Kahan bidiagonalization algorithm has been widely used in solving leastsquares problems and in the computation of the… 
2012
2012
Extended Lanczos Bidiagonalization for Dimension Reduction in Information Retrieval
We describe an extended bidiagonalization scheme designed to compute low-rank approximations of very large data matrices. Its… 
2006
2006
Lanczos tridiagonalization, Golub‐Kahan bidiagonalization and coreproblem
Consider an orthogonally invariant linear approximation problem Ax ≈ b. In [8] it is proved that the partial upper… 
2005
2005
A High Performance C Package for Tridiagonalization of Complex Symmetric Matrices
Block algorithms have better performance than scalar and single vector algorithms due to their exploitation of memory hierarchy… 
1997
1997
Low rank matrix approximation using the Lanczos Bidiagonalization Process
. Low rank approximation of large and/or sparse matrices is important in many ap plications. We show that good low rank matrix… 
1994
1994
Parallel Tri- and Bi-Diagonalization of Bordered Bidiagonal Matrices
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