sparse matrix


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sparse matrix

[′spärs ′mā·triks]
(mathematics)
A matrix most of whose entries are zeros.
McGraw-Hill Dictionary of Scientific & Technical Terms, 6E, Copyright © 2003 by The McGraw-Hill Companies, Inc.
References in periodicals archive ?
--(H, [P.sub.R], [P.sub.C]) [left arrow] DA --Permuting the columns of a sparse matrix:
For the asymptotic analysis, we assume the length of signal n [right arrow] [infinity] and the designed sparse matrix is random.
DAVIS, University of Florida Sparse Matrix Collection, available online at http://www.cise.ufl.edu/~davis/sparse/, NA Digest, Vol.
In this paper, the sparse matrix triple compression storage is used for the Frechet derivative matrix, and only nonzero elements in (10), (11), and (12) and their row and column indexes are stored, solving the storage cost deriving from the Frechet derivative matrix in the framework of the inexact Newton method.
(1) Decompose the matrix of subway passenger flow into a low-rank matrix and a sparse matrix, filter the sparse matrix decomposed by the improved RPCA, and then acquire the anomaly matrix.
HU, The University of Florida sparse matrix collection, ACM Trans.
The above stiffness matrices are sparse matrices and the distributions of the matrix elements in the sparse matrix can be understood through the above expressions.
In order to assess the applicability, scalability, and performance of MPMSC scheme for solving general large sparse linear systems, seven matrices from the University of Florida sparse matrix collection, compare [37], have been considered.
According to the definition of Gram matrix, Gram matrix is the product of measurement matrix and sparse matrix. Therefore, the optimal measurement matrix can be directly derived from the optimal Gram matrix.
Currently, researchers propose many optimized methods for the scale-free networks model by using sparse matrix vector multiplication to construct scale-free networks [16], using the internal weighted average method to calculate the configuration parameters of scale-free networks [17], and using boosting regression algorithm and Bayesian algorithm to construct prior information and establish the scale-free networks based on prior information [18].
To improve the calculation speed, the nuclear system analysis code must be equipped with a faster unsymmetrical sparse matrix solver for the system equations, which could cost nearly half the time during the total calculation.