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1-5 of 5 Reviews about "
Singular Value Decomposition (G.1.3...)
":
Date Reviewed
An improved parallel singular value algorithm and its implementation for multicore hardware
Haidar A., Kurzak J., Luszczek P. SC13 (Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, CO, Nov 17-22, 2013) 1-12, 2013. Type: Proceedings
The singular value decomposition (SVD) has numerous applications, including signal processing, data compression, principal component analysis (PCA), pattern recognition, and so on. Many applications involve large-size data matrices; ho...
Mar 25 2014
Fast algorithms for approximating the singular value decomposition
Menon A., Elkan C. ACM Transactions on Knowledge Discovery from Data 5(2): 1-36, 2011. Type: Article
In this paper, the authors address generating a low-rank approximation to an existing matrix, which is close to the original matrix in some sense. Such approximations arise in a number of application areas, including semantic analysis,...
May 6 2011
The generalized singular value decomposition and the method of particular solutions
Betcke T. SIAM Journal on Scientific Computing 30(3): 1278-1295, 2008. Type: Article
In this paper, the author considers the solution of the eigenvalue problem for differential operators in a bounded region in the plane, using the method of particular solutions (MPS) (sometimes called the point matching method). Betcke...
Mar 20 2009
A μ approach to robust stability analysis of
n
D discrete systems
Xu L., Wu Q., Lin Z., Anazawa Y. Multidimensional Systems and Signal Processing 15(3): 277-293, 2004. Type: Article
This paper develops a stability analysis technique for
n
-dimensional linear systems that exploits MATLAB capabilities. The principal component of such a system is its system matrix
A
, which is squa...
Nov 4 2005
Algorithms for computing the QR decomposition of a set of matrices with common columns
Yanev P., Foschi P., Kontoghiorghes . Algorithmica 39(1): 83-93, 2004. Type: Article
The subject of QR factorization is central to much of the linear parameter estimation technology. This paper considers algorithms for computing QR matrix decomposition in the case of a sequence of matrices that have common columns. Thi...
Jun 1 2005
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