Singular value decomposition svd

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Reducing Memory Cost of Exact Diagonalization using Singular Value Decomposition [PDF]

, 2011
We present a modified Lanczos algorithm to diagonalize lattice Hamiltonians with dramatically reduced memory requirements, {\em without restricting to variational ansatzes}. The lattice of size $N$ is partitioned into two subclusters.
/SLAC +5 more
core +2 more sources

Robust Audio Watermarking Using Graph-based Transform and Singular Value Decomposition [PDF]

International Symposium on Telecommunications, 2020
Graph-based Transform (GT) has been recently leveraged successfully in signal processing domain, specifically for compression purposes. In this paper, we employ the GBT, as well as the Singular Value Decomposition (SVD) with the goal to improve the ...
Majid Farzaneh, Rahil Mahdian Toroghi
semanticscholar +1 more source

The Hessian biased singular value decomposition method for optimization and analysis of force fields [PDF]

, 1996
We present methodology (HBFF/SVD) for optimizing the form and parameters of force fields (FF) for molecular dynamics simulations through utilizing information about properties such as the geometry, Hessian, polarizability, stress (crystals), and elastic ...
Dasgupta, Siddharth +2 more
core +1 more source

Generalizations of singular value decomposition to dual-numbered matrices [PDF]

Linear and multilinear algebra, 2020
We present two generalizations of Singular Value Decomposition from real-numbered matrices to dual-numbered matrices. We prove that every dual-numbered matrix has both types of SVD.
Ran Gutin
semanticscholar +1 more source

Singular Value Decomposition Approaches in A Correspondence Analysis with The Use of R

Folia Oeconomica Stetinensia, 2018
The aim of a correspondence analysis is the graphical representation of the categories of variables in one frame of reference. This visualization is possible due to the decomposition of the basic matrix with the use of Singular Value Decomposition (SVD).
Brzezińska Justyna
doaj +1 more source

DEKOMPOSISI NILAI SINGULAR PADA SISTEM PENGENALAN WAJAH

Jurnal Matematika, 2012
Dekomposisi Nilai Singular atau Singular Value Decomposition (SVD) merupakan salah satu cara untuk menyatakan Principal Component Analysis (PCA).
Beni Utomo
doaj +1 more source

Enhancing artificial neural network learning efficiency through Singular value decomposition for solving partial differential equations

Results in Applied Mathematics
Partial differential equations (PDEs) hold significant potential for modelling natural phenomena. It is essential to look at a practical way to solve the PDEs.
Alfi Bella Kurniati +3 more
doaj +1 more source

Quaternion Singular Value Decomposition based on Bidiagonalization to a Real Matrix using Quaternion Householder Transformations

, 2006
We present a practical and efficient means to compute the singular value decomposition (svd) of a quaternion matrix A based on bidiagonalization of A to a real bidiagonal matrix B using quaternionic Householder transformations.
Anderson +12 more
core +3 more sources

Fast multilinear Singular Values Decomposition for higher-order Hankel tensors [PDF]

, 2014
International audienceThe Higher-Order Singular Value Decomposition (HOSVD) is a possible generalization of the Singular Value Decomposition (SVD) to tensors, which have been successfully applied in various domains.
Boizard, Maxime +3 more
core +3 more sources

SVD-phy: improved prediction of protein functional associations through singular value decomposition of phylogenetic profiles

Bioinform., 2015
Summary: A successful approach for predicting functional associations between non-homologous genes is to compare their phylogenetic distributions.
Andrea Franceschini, Jianyi Lin, C. V. Mering, L. Jensen +3 more
semanticscholar +1 more source

singular value decomposition
svd
physics