Results 31 to 40 of about 34,257 (101)
Two-way bidiagonalization scheme for downdating the singular-value decomposition
Linear Algebra and its Applications, 1995 Downdating of a matrix means the deletion of an existing row of this matrix. It is shown that the problem of downdating a row in the singular value decomposition of a matrix can be transformed into a problem of bidiagonalizing a diagonal matrix bordered by a column and then diagonalizing this bidiagonal matrix. For the bidiagonalization of a rank-\(r\)
Park, Haesun, Van Huffel, Sabine
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High Relative Accuracy Computations With Covariance Matrices of Order Statistics
Mathematical Methods in the Applied Sciences, Volume 49, Issue 11, Page 11794-11810, 30 July 2026.ABSTRACT In many statistical applications, numerical computations with covariance matrices need to be performed. The error made when performing such numerical computations increases with the condition number of the covariance matrix, which is related to the number of variables and the strength of the correlation between the variables. In a recent work,
Juan Baz +3 more
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Coupling Intuitive Physics Into Deep Learning for Soil Moisture Flow Processes Learning
Water Resources Research, Volume 62, Issue 4, April 2026.Abstract Soil water flow processes in the unsaturated zone support ecosystems and regulate water, energy, and biogeochemical cycles. Recently, deep learning (DL) approaches have significantly advanced soil moisture (SM) prediction tasks yet still challenging to interpret.
Leilei He +6 more
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A Fixed‐Point Discrepancy Approach to Tikhonov Regularization Parameter Selection
Journal of Mathematics, Volume 2026, Issue 1, 2026.This paper presents a unified comparative study of Tikhonov regularization parameter selection for linear ill‐posed problems with both data noise and operator perturbations. We integrate the generalized discrepancy principle (GDP), its fixed‐point formulation (GDP–FP), and the Arnoldi–Neubauer projection approach (PGDP–AN) within a common analytical ...
Maged Alkilayh, Smritijit Sen
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High Relative Accuracy With Collocation Matrices of q$$ q $$‐Jacobi Polynomials
Numerical Linear Algebra with Applications, Volume 32, Issue 1, February 2025.ABSTRACT Little q$$ q $$‐Jacobi polynomials belong to the field of quantum calculus. This article obtains the bidiagonal decomposition of the collocation matrices of these polynomials, showing that, in many cases, it can be constructed to high relative accuracy (HRA).
Jorge Delgado +2 more
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Euclidean decompositions of hyperbolic manifolds and their duals [PDF]
, 2007 Epstein and Penner constructed in [EP88] the Euclidean decomposition of a non-compact hyperbolic n-manifold of finite volume for a choice of cusps, n >= 2. The manifold is cut along geodesic hyperplanes into hyperbolic ideal convex polyhedra.
Lukac, Sascha Georg
core
Krylov Subspace Based FISTA‐Type Methods for Linear Discrete Ill‐Posed Problems
Numerical Linear Algebra with Applications, Volume 32, Issue 1, February 2025.ABSTRACT Several iterative soft‐thresholding algorithms, such as FISTA, have been proposed in the literature for solving regularized linear discrete inverse problems that arise in various applications in science and engineering. These algorithms are easy to implement, but their rates of convergence may be slow.
Alessandro Buccini +3 more
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Bidiagonal factorizations with some parameters equal to zero [PDF]
, 2011 Motivated by the results of Fiedler and Markham [2], we provide necessary and sufficient conditions for a matrix to have a bidiagonal factorization with some of the parameters of the bidiagonal factors equal to ...
Huang, Rong +3 more
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Minimum‐Time Output Control by Reference Interpolation for Linear Multivariable Systems
IET Control Theory &Applications, Volume 19, Issue 1, January/December 2025.For linear multivariable systems, we consider the minimum‐time output control problem with explicit constraints on the inputs' intensity and piecewise‐constant controls. We face the problem by imposing that each output passes through a given set of points.
Luigi D'Alfonso +2 more
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Accurate bidiagonal factorization of quantum Hilbert matrices [PDF]
, 2023 A bidiagonal decomposition of quantum Hilbert matrices is obtained and the total positivity of these matrices is proved. This factorization is used to get accurate algebraic computations with these matrices. The numerical errors due to imprecise computer
Rubio, B., Mainar, E., Peña, J.M.
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