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Singular value decomposition

Known as: SVD, Singular-value decomposition, SV decomposition 
In linear algebra, the singular value decomposition (SVD) is a factorization of a real or complex matrix. It is the generalization of the… 
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Papers overview

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2009
2009
Recommender Systems are introduced as an intelligent technique to deal with the problem of information and product overload… 
2007
2007
Enhancing the connectivity of wireless sensor networks is necessary to avoid the occurrence of coverage gaps. In this paper, we… 
Highly Cited
2006
Highly Cited
2006
In this paper we show how approximate matrix factorisations can be used to organise document summaries returned by a search… 
2005
2005
The problem of two-channel constrained least squares (CLS) filtering under various sets of constraints is considered, and a… 
2002
2002
Load instructions diminish processor performance in two ways. First, due to the continuously widening gap between CPU and memory… 
2000
2000
A face identification method based on singular value decomposition (SVD) and data fusion is proposed in this paper. The singular… 
1984
1984
Systolic arrays for determining the Singular Value Decomposition of a mxn, m > n, matrix A of bandwidth w are presented. After A… 
1984
1984
Architectures, algorithms, and applications for systolic processors are described with attention to the realization of parallel… 
Highly Cited
1983
Highly Cited
1983
In the recent years, the resolving capability of passive array processing has been greatly improved by the so-called high… 
1982
1982
We propose a systolic architecture for computing a singular value decomposition of an m x n matrix, where $m \geq n$. Our…