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Singular Value Decomposition
"... Thin Film Transistor Liquid Crystal Displays (TFTLCDs) have become increasingly popular and dominant as display devices. Surface defects on TFT panels not only cause visual failure, but result in electrical failure and loss of LCD operational functionally. In this paper, we propose a global approac ..."
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of textures. It is based on a global image reconstruction scheme using the singular value decomposition (SVD). Taking the image as a matrix of pixels, the singular values on the decomposed diagonal matrix represent different degrees of detail in the textured image. By selecting the proper singular values
Perturbation Theory for the Singular Value Decomposition
 IN SVD AND SIGNAL PROCESSING, II: ALGORITHMS, ANALYSIS AND APPLICATIONS
, 1990
"... The singular value decomposition has a number of applications in digital signal processing. However, the the decomposition must be computed from a matrix consisting of both signal and noise. It is therefore important to be able to assess the effects of the noise on the singular values and singular v ..."
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Cited by 49 (0 self)
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The singular value decomposition has a number of applications in digital signal processing. However, the the decomposition must be computed from a matrix consisting of both signal and noise. It is therefore important to be able to assess the effects of the noise on the singular values and singular
I. SINGULAR VALUE DECOMPOSITION
"... Abstract — We review the basic results on: (1) the singular value decomposition (SVD); (2) sensitivity and conditioning of solutions of linear systems of equations; (3) regularization; and (4) iterative solution of linear systems of equations. These are applied to the specific problem of computing a ..."
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Abstract — We review the basic results on: (1) the singular value decomposition (SVD); (2) sensitivity and conditioning of solutions of linear systems of equations; (3) regularization; and (4) iterative solution of linear systems of equations. These are applied to the specific problem of computing
On the singular values and eigenvalues of . . .
, 2010
"... The Fox–Li operator is a convolution operator over a finite interval with a special highly oscillatory kernel. It plays an important role in laser engineering. However, the mathematical analysis of its spectrum is still rather incomplete. In this expository paper we survey part of the state of the ..."
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of the art, and our emphasis is on showing how standard Wiener–Hopf theory can be used to obtain insight into the behaviour of the singular values of the Fox–Li operator. In addition, several approximations to the spectrum of the Fox–Li operator are discussed and results on the singular values
The singular values of the GOE
, 2015
"... As a unifying framework for examining several properties that nominally involve eigenvalues, we present a particular structure of the singular values of the Gaussian orthogonal ensemble (GOE): the evenlocation singular values are distributed as the positive eigenvalues of a Gaussian ensemble with ..."
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As a unifying framework for examining several properties that nominally involve eigenvalues, we present a particular structure of the singular values of the Gaussian orthogonal ensemble (GOE): the evenlocation singular values are distributed as the positive eigenvalues of a Gaussian ensemble
Robust Singular Value
"... The singular value decomposition of a rectangular data matrix can be used to understand the structure of the data and give insight into the relationships of the row and column factors. For example, the rows linked to the rows might be experimental conditions of temperature and the experimental condi ..."
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The singular value decomposition of a rectangular data matrix can be used to understand the structure of the data and give insight into the relationships of the row and column factors. For example, the rows linked to the rows might be experimental conditions of temperature and the experimental
The Singular Value Decomposition for Polynomial Systems
, 1995
"... This paper introduces singular value decomposition (SVD) algorithms for some standard polynomial computations, in the case where the coefficients are inexact or imperfectly known. We first give an algorithm for computing univariate GCD's which gives exact results for interesting nearby problems ..."
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Cited by 88 (9 self)
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This paper introduces singular value decomposition (SVD) algorithms for some standard polynomial computations, in the case where the coefficients are inexact or imperfectly known. We first give an algorithm for computing univariate GCD's which gives exact results for interesting nearby
Generalized Singular Value Decomposition
"... In Linear Discriminant Analysis (LDA), a dimension reducing linear transformation is found in order to better distinguish clusters from each other in the reduced dimensional space. However, LDA has a limitation that one of the scatter matrices is required to be nonsingular and the nonlinearly cluste ..."
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clustered structure is not easily captured. We propose a nonlinear discriminant analysis based on kernel functions and the generalized singular value decomposition called KDA/GSVD, which is a nonlinear extension of LDA and works regardless of the nonsingularity of the scatter matrices in either the input
Randomized Singular Value Projection
"... Abstract—Affine rank minimization algorithms typically rely on calculating the gradient of a data error followed by a singular value decomposition at every iteration. Because these two steps are expensive, heuristic approximations are often used to reduce computational burden. To this end, we propos ..."
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Cited by 1 (1 self)
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Abstract—Affine rank minimization algorithms typically rely on calculating the gradient of a data error followed by a singular value decomposition at every iteration. Because these two steps are expensive, heuristic approximations are often used to reduce computational burden. To this end, we
Singular Values using Cholesky Decomposition
"... Abstract—In this paper two ways to compute singular values are presented which use Cholesky decomposition as their basic operation. I. ..."
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Abstract—In this paper two ways to compute singular values are presented which use Cholesky decomposition as their basic operation. I.
Results 11  20
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