The singular value decomposition (SVD) goes back to the beginning of this century. In a paper of Beltrami [3] it was shown for the first time that any n x n matrix A can be diagonalized via orthogonal row and column transformations. ..
AbstractThe Partial Singular Value Decomposition (PSVD) subroutine computes a basis of the left and/...
Singular value decomposition is a promising tool in the analysis and control of process systems. Sin...
© 2015 Elsevier Inc. All rights reserved. In this letter a new variational principle to the matrix s...
We shall consider a form of matrix factorization known as singular value decomposition (SVD) that is...
Let A be an m x n matrix with m greater than or equal to n. Then one form of the singular-value deco...
This volume is an outgrowth of the 2nd International Workshop on SVD and Signal Processing which was...
The Singular Value Decomposition (SVD) is very well known. We provide an intuitive proof for real ma...
Matrix Singular Value Decomposition (SVD) and its application to problems in signal processing is ex...
The ordinary Singular Value Decomposition (SVD) is widely used in statistical and signal processing...
The singular value decomposition (SVD) is a fundamental matrix decomposition in linear algebra. It i...
This paper surveys the contributions of five mathematicians\,---\,Eugenio Beltrami (1835--1899), Cam...
A novel algorithm for calculating the singular value decomposition (SVD) of a polynomial matrix is p...
A novel algorithm for calculating the singular value decomposition (SVD) of a polynomial matrix is p...
The paper considers the singular value decomposition (SVD) of a general matrix. Some immediate appli...
Singular value decomposition (SVD) is a useful tool in functional data analysis (FDA). Compared to p...
AbstractThe Partial Singular Value Decomposition (PSVD) subroutine computes a basis of the left and/...
Singular value decomposition is a promising tool in the analysis and control of process systems. Sin...
© 2015 Elsevier Inc. All rights reserved. In this letter a new variational principle to the matrix s...
We shall consider a form of matrix factorization known as singular value decomposition (SVD) that is...
Let A be an m x n matrix with m greater than or equal to n. Then one form of the singular-value deco...
This volume is an outgrowth of the 2nd International Workshop on SVD and Signal Processing which was...
The Singular Value Decomposition (SVD) is very well known. We provide an intuitive proof for real ma...
Matrix Singular Value Decomposition (SVD) and its application to problems in signal processing is ex...
The ordinary Singular Value Decomposition (SVD) is widely used in statistical and signal processing...
The singular value decomposition (SVD) is a fundamental matrix decomposition in linear algebra. It i...
This paper surveys the contributions of five mathematicians\,---\,Eugenio Beltrami (1835--1899), Cam...
A novel algorithm for calculating the singular value decomposition (SVD) of a polynomial matrix is p...
A novel algorithm for calculating the singular value decomposition (SVD) of a polynomial matrix is p...
The paper considers the singular value decomposition (SVD) of a general matrix. Some immediate appli...
Singular value decomposition (SVD) is a useful tool in functional data analysis (FDA). Compared to p...
AbstractThe Partial Singular Value Decomposition (PSVD) subroutine computes a basis of the left and/...
Singular value decomposition is a promising tool in the analysis and control of process systems. Sin...
© 2015 Elsevier Inc. All rights reserved. In this letter a new variational principle to the matrix s...