Results 21 to 30 of about 539,466 (113)
Hessenberg, Tridiagonal And Bidiagonal Decomposition
, 2023 Tema ovoga rada su matrice i različite dekompozicije matrica. Dekompozicija matrica je postupak kojim se složena matrica razvija kao produkt više složenih matrica kako bi se olakšala analiza ili rješavanje matematičkih problema.
Dujček, Mateja
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Positive bidiagonal factorization of tetradiagonal Hessenberg matrices [PDF]
, 2023 2023 Acuerdos transformativos CRUERecently, a spectral Favard theorem was presented for bounded banded lower Hessenberg matrices that possess a positive bidiagonal factorization. The paper establishes conditions, expressed in terms of continued fractions,
Mañas Baena, Manuel Enrique +7 more
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The power of bidiagonal matrices [PDF]
Bidiagonal matrices are widespread in numerical linear algebra, not least because of their use in the standard algorithm for computing the singular value decomposition and their appearance as LU factors of tridiagonal matrices.
Higham, Nicholas J.
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Bidiagonal decomposition of totally positive Bernstein‐Vandermonde matrices [PDF]
PAMM, 2007 AbstractThe class of Bernstein‐Vandermonde matrices (a generalization of Vandermonde matrices arising when the monomial basis is replaced by the Bernstein basis) is considered. A convenient ordering of their rows makes these matrices strictly totally positive.
José‐Javier Martínez, Ana Marco
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Total positivity and accurate computations with Gram matrices of Said‐Ball bases
Numerical Linear Algebra with Applications, Volume 30, Issue 6, December 2023., 2023 Abstract In this article, it is proved that Gram matrices of totally positive bases of the space of polynomials of a given degree on a compact interval are totally positive. Conditions to guarantee computations to high relative accuracy with those matrices are also obtained.
E. Mainar, J. M. Peña, B. Rubio
wiley +1 more source
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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Journal of Chemometrics, Volume 37, Issue 10, October 2023., 2023 Abstract In various situations requiring empirical model building from highly multivariate measurements, modelling based on partial least squares regression (PLSR) may often provide efficient low‐dimensional model solutions. In unsupervised situations, the same may be true for principal component analysis (PCA).
Joakim Skogholt +4 more
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High relative accuracy with some special matrices related to Γ and β functions
Numerical Linear Algebra with Applications, Volume 30, Issue 5, October 2023., 2023 Abstract For some families of totally positive matrices using Γ$$ \Gamma $$ and β$$ \beta $$ functions, we provide their bidiagonal factorization. Moreover, when these functions are defined over integers, we prove that the bidiagonal factorization can be computed with high relative accuracy and so we can compute with high relative accuracy their ...
Jorge Delgado, Juan Manuel Peña
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Geophysical Prospecting, Volume 71, Issue 5, Page 847-875, June 2023., 2023 Abstract Non‐linear inversion of controlled source electromagnetic data is non‐unique. Inversion ambiguity and uncertainty grow with model complexity and limitations in sensitivity, for example when imaging deep targets. Uncertainties should be estimated. The best way to do that is by statistical inversion techniques.
Emmanuel Causse
wiley +1 more source
Depth of almost strictly sign regular matrices
Mathematical Methods in the Applied Sciences, Volume 46, Issue 1, Page 732-744, 15 January 2023., 2023 The concept of depth of an almost strictly sign regular matrix is introduced and used to simplify some algorithmic characterizations of these matrices.
Pedro Alonso +3 more
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