Results 11 to 20 of about 607,065 (288)

Explicit expressions for Virasoro singular vectors [PDF]

open access: yesJournal of High Energy Physics
We present two explicit expressions for generic singular vectors of type (r, s) of the Virasoro algebra. These results follow from the paper of Bauer et al. which presented recursive methods to construct the vectors.
Gérard M. T. Watts
doaj   +5 more sources

Sharp error bounds for Ritz vectors and approximate singular vectors [PDF]

open access: yesMathematics of Computation, 2020
We derive sharp bounds for the accuracy of approximate eigenvectors (Ritz vectors) obtained by the Rayleigh-Ritz process for symmetric eigenvalue problems. Using information that is available or easy to estimate, our bounds improve the classical Davis-Kahan
Nakatsukasa, Yuji
openaire   +6 more sources

Length Reduction of Singular Spectrum Analysis With Guarantee Exact Perfect Reconstruction via Block Sliding Approach

open access: yesIEEE Access, 2020
The conventional singular spectrum analysis is to divide a signal into segments where there is only one non-overlapping point between two consecutive segments.
Xinpeng Wang, Bingo Wing-Kuen Ling
doaj   +1 more source

Singular Vectors and Time-Dependent Normal Modes of a Baroclinic Wave-Mean Oscillation [PDF]

open access: yes
Linear disturbance growth is studied in a quasigeostrophic baroclinic channel model with several thousand degrees of freedom. Disturbances to an unstable, nonlinear wave-mean oscillation are analyzed, allowing the comparison of singular vectors and time ...
Wolfe, Christopher L.   +1 more
core   +6 more sources

On the singular value decomposition of (skew-)involutory and (skew-)coninvolutory matrices

open access: yesSpecial Matrices, 2020
The singular values σ > 1 of an n × n involutory matrix A appear in pairs (σ, 1σ{1 \over \sigma }). Their left and right singular vectors are closely connected. The case of singular values σ = 1 is discussed in detail. These singular values may appear in
Faßbender Heike, Halwaß Martin
doaj   +1 more source

An Out of Memory tSVD for Big-Data Factorization

open access: yesIEEE Access, 2020
Singular value decomposition (SVD) is a matrix factorization method widely used for dimension reduction, data analytics, information retrieval, and unsupervised learning.
Hector Carrillo-Cabada   +4 more
doaj   +1 more source

Singularity Problem for Interacting Massive Vectors

open access: yesPhysical Review Letters, 2022
Interacting massive spin-1 fields have been widely used in cosmology and particle physics. We obtain a new condition on the validity of the classical limit of these theories related to the non-trivial constraints that exist for vector field components.
Zong-Gang Mou, Hong-Yi Zhang
openaire   +3 more sources

FUSION AND THE NEVEU-SCHWARZ SINGULAR VECTORS [PDF]

open access: yesInternational Journal of Modern Physics A, 1994
Bauer, di Francesco, Itzykson and Zuber recently proposed an algorithm to construct all singular vectors of the Virasoro algebra. It is based on the decoupling of (already known) singular fields in the fusion process. We show the extension of their algorithm to the Neveu-Schwarz superalgebra.
Benoit, Louis, Saint-Aubin, Yvan
openaire   +2 more sources

SINGULAR VECTORS OF THE TOPOLOGICAL CONFORMAL ALGEBRA [PDF]

open access: yesInternational Journal of Modern Physics A, 1996
A general construction is found for “topological” singular vectors of the twisted N=2 superconformal algebra. It demonstrates many parallels with the known construction for affine sℓ(2) singular vectors due to Malikov–Feigin–Fuchs, but is formulated independently of the latter.
Semikhatov, A. M., Tipunin, I. Yu.
openaire   +2 more sources

DIGITAL WATERMARKING IN THE SINGULAR VECTOR DOMAIN [PDF]

open access: yesInternational Journal of Image and Graphics, 2008
Many current watermarking algorithms insert data in the spatial or transform domains like the discrete cosine, the discrete Fourier, and the discrete wavelet transforms. In this paper, we present a data-hiding algorithm that exploits the singular value decomposition (SVD) representation of the data.
Rashmi Agarwal, M. S. Santhanam
openaire   +3 more sources

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