Results 21 to 30 of about 1,499,755 (333)
A Novel Partitioning Method for Accelerating the Block Cimmino Algorithm [PDF]
, 2018 We propose a novel block-row partitioning method in order to improve the convergence rate of the block Cimmino algorithm for solving general sparse linear systems of equations.
Aykanat, Cevdet +2 more
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Block-adaptive Cross Approximation of Discrete Integral Operators [PDF]
, 2019 In this article we extend the adaptive cross approximation (ACA) method known for the efficient approximation of discretisations of integral operators to a block-adaptive version.
Bauer, M., Bebendorf, M.
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MATRIX SUBADDITIVITY INEQUALITIES AND BLOCK-MATRICES [PDF]
International Journal of Mathematics, 2009 We give a number of subadditivity results and conjectures for symmetric norms, matrices and block-matrices. Let A, B, Z be matrices of same size and suppose that A, B are normal and Z is expansive, i.e. Z*Z ≥ I. We conjecture that [Formula: see text] for all non-negative concave function f on [0,∞) and all symmetric norms ‖ · ‖ (in particular for all ...
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Symmetric indefinite triangular factorization revealing the rank profile matrix [PDF]
, 2018 We present a novel recursive algorithm for reducing a symmetric matrix to a triangular factorization which reveals the rank profile matrix. That is, the algorithm computes a factorization $\mathbf{P}^T\mathbf{A}\mathbf{P} = \mathbf{L}\mathbf{D}\mathbf{L}^
Dumas, Jean-Guillaume, Pernet, Clement
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Practical method to solve large least squares problems using Cholesky decomposition
Geodesy and Cartography, 2015 In Geomatics, the method of least squares is commonly used to solve the systems of observation equations for a given number of unknowns. This method is basically implemented in case of having number observations larger than the number of unknowns ...
Ghadi Younis
doaj +1 more source
Deep Subspace Clustering with Block Diagonal Constraint
Applied Sciences, 2020 The deep subspace clustering method, which adopts deep neural networks to learn a representation matrix for subspace clustering, has shown good performance.
Jing Liu, Yanfeng Sun, Yongli Hu
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Eigenvalues of block structured asymmetric random matrices [PDF]
, 2015 We study the spectrum of an asymmetric random matrix with block structured variances. The rows and columns of the random square matrix are divided into $D$ partitions with arbitrary size (linear in $N$).
Aljadeff, Johnatan +2 more
core +1 more source
Sensors, 2015 Aiming at addressing the problem of high computational cost of the traditional Kalman filter in SINS/GPS, a practical optimization algorithm with offline-derivation and parallel processing methods based on the numerical characteristics of the system is ...
Shaoxing Hu +3 more
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Lossy Compression using Adaptive Polynomial Image Encoding
Advances in Electrical and Computer Engineering, 2021 In this paper, an efficient lossy compression approach using adaptive-block polynomial curve-fitting encoding is proposed. The main idea of polynomial curve fitting is to reduce the number of data elements in an image block to a few coefficients.
OTHMAN, S. +3 more
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Memory-usage advantageous block recursive matrix inverse [PDF]
Applied Mathematics and Computation, 2018 The inversion of extremely high order matrices has been a challenging task because of the limited processing and memory capacity of conventional computers. In a scenario in which the data does not fit in memory, it is worth to consider exchanging less memory usage for more processing time in order to enable the computation of the inverse which ...
Iria C.S. Cosme +3 more
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