AbstractThis paper reports several parallel singular value decomposition (SVD) algorithms on the hypercube and shuffle-exchange SIMD computers. Unlike previously published hypercube SVD algorithms which map a column pair of a matrix onto a processor, the algorithms presented in this paper map a matrix column pair onto a column of processors. In this way, a further reduction in time complexity is achieved. The paper also introduces the concept of two-dimensional shuffle-exchange networks, and corresponding SVD algorithms for one-dimensional and two-dimensional shuffle-exchange computers are developed
Multi-dimensional digital signal processing such as image processing and image reconstruction involv...
Masters ThesisThe Singular Value Decomposition (SVD) is an important matrix factorization with appli...
Abstract. Approximation of matrices using the Singular Value Decom-position (SVD) plays a central ro...
AbstractThis paper reports several parallel singular value decomposition (SVD) algorithms on the hyp...
Singular value decomposition (SVD) is used in many applications such as real-time signal processing ...
We present a stream algorithm for the Singular-Value Decomposition (SVD) of anM X N matrix A. Our al...
In this work an efficient model for parallel computing, called Shuffled Mesh (SM), is in-troduced. T...
The increasing popularity of singular value decomposition algorithms, used as a tool in many areas ...
Abstract-As a useful tool for dimensionality reduction, Singular Value Decomposition (SVD) plays an ...
Systolic arrays for determining the singular value decomposition of a mxn, m n, matrix A of bandwid...
We describe a new Jacobi ordering for parallel computation of SVD problems. The ordering uses the hi...
We describe three new Jacobi orderings for parallel computation of SVD problems on tree architecture...
We describe three new Jacobi orderings for parallel computation of SVD problems on tree architecture...
This thesis presents a systolic algorithm for the SVD of arbitrary complex matrices, based on the cy...
The singular value decomposition (SVD) is a fundamental matrix decomposition in linear algebra. It i...
Multi-dimensional digital signal processing such as image processing and image reconstruction involv...
Masters ThesisThe Singular Value Decomposition (SVD) is an important matrix factorization with appli...
Abstract. Approximation of matrices using the Singular Value Decom-position (SVD) plays a central ro...
AbstractThis paper reports several parallel singular value decomposition (SVD) algorithms on the hyp...
Singular value decomposition (SVD) is used in many applications such as real-time signal processing ...
We present a stream algorithm for the Singular-Value Decomposition (SVD) of anM X N matrix A. Our al...
In this work an efficient model for parallel computing, called Shuffled Mesh (SM), is in-troduced. T...
The increasing popularity of singular value decomposition algorithms, used as a tool in many areas ...
Abstract-As a useful tool for dimensionality reduction, Singular Value Decomposition (SVD) plays an ...
Systolic arrays for determining the singular value decomposition of a mxn, m n, matrix A of bandwid...
We describe a new Jacobi ordering for parallel computation of SVD problems. The ordering uses the hi...
We describe three new Jacobi orderings for parallel computation of SVD problems on tree architecture...
We describe three new Jacobi orderings for parallel computation of SVD problems on tree architecture...
This thesis presents a systolic algorithm for the SVD of arbitrary complex matrices, based on the cy...
The singular value decomposition (SVD) is a fundamental matrix decomposition in linear algebra. It i...
Multi-dimensional digital signal processing such as image processing and image reconstruction involv...
Masters ThesisThe Singular Value Decomposition (SVD) is an important matrix factorization with appli...
Abstract. Approximation of matrices using the Singular Value Decom-position (SVD) plays a central ro...