Results 11 to 20 of about 8,808,141 (242)

Total Least Squares Methods [PDF]

open access: yesWIREs Computational Statistics, 2010
Recent advances in total least squares approaches for solving various errors-in-variables modeling problems are reviewed, with emphasis on the following generalizations: 1.
Markovsky, Ivan   +2 more
core   +4 more sources

Overview of total least squares methods [PDF]

open access: yesSignal Processing, 2007
We review the development and extensions of the classical total least squares method and describe algorithms for its generalization to weighted and structured approximation problems.
Markovsky, Ivan, Van Huffel, Sabine
core   +5 more sources

On weighted structured total least squares [PDF]

open access: yes, 2006
In this contribution we extend the result of (Markovsky et. al, SIAM J. of Matrix Anal. and Appl., 2005) to the case of weighted cost function. It is shown that the computational complexity of the proposed algorithm is preserved linear in the sample size
Markovsky, Ivan   +3 more
core   +4 more sources

Fast Algorithms for Structured Least Squares and Total Least Squares Problems

open access: yesJournal of Research of the National Institute of Standards and Technology, 2006
We consider the problem of solving least squares problems involving a matrix M of small displacement rank with respect to two matrices Z(1) and Z(2). We develop formulas for the generators of the matrix (MM)-M-H in terms of the generators of M and show ...
Kalsi, Anoop; O'Leary, Dianne P.
core   +3 more sources

Regularization by Truncated Total Least Squares [PDF]

open access: yesSIAM Journal on Scientific Computing, 1997
The truncated total least squares (TLS) technique is investigated. It filters the solution by truncating the small singular values of the TLS matrix. The given iterative algorithm for computing the truncated TLS solution bases on Lanczos bidiagonalization. The algorithm is efficient when the number of retained singular values is small compared with the
Ricardo D. Fierro   +3 more
openaire   +1 more source

Orthogonal Projection and Total Least Squares [PDF]

open access: yesNumerical Linear Algebra with Applications, 1993
AbstractOverdetermined linear systems often arise in applications such as signal processing and modern communication. When the overdetermined system of linear equations AX ≈︁ B has no solution, compatibility may be restored by an orthogonal projection method. The idea is to determine an orthogonal projection matrix P by some method M such that [Ã B̃] =
Ricardo D. Fierro, James R. Bunch
openaire   +3 more sources

Tikhonov Regularization and Total Least Squares [PDF]

open access: yesSIAM Journal on Matrix Analysis and Applications, 1999
The regularized total least squares (TLS) method of the TLS problem is introduced and its regularizing properties are studied. It is also proved that, in certain cases, the new method is superior to standard regularization methods.
Gene H. Golub   +2 more
openaire   +3 more sources

High-performance numerical algorithms and software for structured total least squares [PDF]

open access: yes, 2005
We present a software package for structured total least squares approximation problems. The allowed structures in the data matrix are block-Toeplitz, block-Hankel, unstructured, and exact.
Van Huffel, S.   +3 more
core   +2 more sources

Total Least Squares Phase Retrieval

open access: yesIEEE Transactions on Signal Processing, 2022
We address the phase retrieval problem with errors in the sensing vectors. A number of recent methods for phase retrieval are based on least squares (LS) formulations which assume errors in the quadratic measurements. We extend this approach to handle errors in the sensing vectors by adopting the total least squares (TLS) framework that is used in ...
Gupta, Sidharth   +2 more
openaire   +2 more sources

Total Least Squares Registration of 3D Surfaces

open access: yesInternational Journal of Environment and Geoinformatics, 2015
Co-registration of point clouds of partially scanned objects is the first step of the 3D modeling workflow. The aim of co-registration is to merge the overlapping point clouds by estimating the spatial transformation parameters.
Umut Aydar, M. Orhan Altan
doaj   +1 more source

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