Results 71 to 80 of about 256,417 (191)

Sorting and ordering sparse linear systems [PDF]

Transformations of sparse linear systems by row-column permutations are considered and various algorithms are constructed to transform arbitrary symmetric positive definite sparse matrices, as well as matrices in band form, doubly bordered band form, and
Tewarson, R. P.
core   +1 more source

Invertibility of sparse non-Hermitian matrices

Advances in Mathematics, 2017
46 pages, minor changes in V3.
Basak, Anirban, Rudelson, Mark
openaire   +3 more sources

Logarithmically sparse symmetric matrices

Beiträge zur Algebra und Geometrie / Contributions to Algebra and Geometry
AbstractA positive definite matrix is called logarithmically sparse if its matrix logarithm has many zero entries. Such matrices play a significant role in high-dimensional statistics and semidefinite optimization. In this paper, logarithmically sparse matrices are studied from the point of view of computational algebraic geometry: we present a formula
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Nonuniform Sparse Recovery with Subgaussian Matrices

Electronic Transactions on Numerical Analysis, 2010
Compressive sensing predicts that sufficiently sparse vectors can be recovered from highly incomplete information. Efficient recovery methods such as $\ell_1$-minimization find the sparsest solution to certain systems of equations. Random matrices have become a popular choice for the measurement matrix.
Ulas Ayaz, Holger Rauhut
openaire   +3 more sources

Saliency Detection Using Sparse and Nonlinear Feature Representation

The Scientific World Journal, 2014
An important aspect of visual saliency detection is how features that form an input image are represented. A popular theory supports sparse feature representation, an image being represented with a basis dictionary having sparse weighting coefficient ...
Shahzad Anwar, Qingjie Zhao, Muhammad Farhan Manzoor, Saqib Ishaq Khan   +3 more
doaj   +1 more source

Linear Transformations for Randomness Extraction [PDF]

, 2012
Information-efficient approaches for extracting randomness from imperfect sources have been extensively studied, but simpler and faster ones are required in the high-speed applications of random number generation.
Bruck, Jehoshua, Zhou, Hongchao
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An introduction to Sparse Matrices

Irish Mathematical Society Bulletin, 1985
The author gives a concise introduction to sparse matrices. First, the history and goals of sparse matrices are outlined. (The reviewer's book Sparse matrices (1973; Zbl 0262.65021) which was the first text in this area is inadvertently not mentioned.) The second part of this paper deals with a description of storage schemes.
openaire   +2 more sources

Alternating Direction Method of Multipliers for Sparse and Low-Rank Decomposition Based on Nonconvex Nonsmooth Weighted Nuclear Norm

IEEE Access, 2018
Sparse and low-rank decomposition (SLRD) poses a big challenge in many fields. The existing methods are used to solve SLRD problem via formulating approximations of sparse and low-rank matrices.
Zhenzhen Yang, Zhen Yang, Deren Han
doaj   +1 more source

Compressed Sensing and Parallel Acquisition

, 2016
Parallel acquisition systems arise in various applications in order to moderate problems caused by insufficient measurements in single-sensor systems. These systems allow simultaneous data acquisition in multiple sensors, thus alleviating such problems ...
Adcock, Ben, Chun, Il Yong
core  

A Monte Carlo Evaluation of Weighted Community Detection Algorithms

Frontiers in Neuroinformatics, 2016
The past decade has been marked with a proliferation of community detection algorithms that aim to organize nodes (e.g., individuals, brain regions, variables) into modular structures that indicate subgroups, clusters, or communities.
Kathleen Gates, Teague Henry, Doug Steinley, Damien Fair   +3 more
doaj   +1 more source