Results 1 to 10 of about 869,856 (135)
Mathematical Modelling and Control, 2023 This paper investigated the Kronecker product (KP) decomposition of the Boolean matrix and analyzed the topological structure of Kronecker product Boolean networks (KPBNs).
Xiaomeng Wei, Haitao Li, Guodong Zhao
doaj +1 more source
Singular Value Decomposition of Spatial Matrices
Современные информационные технологии и IT-образование, 2022 Singular value decomposition is a basic building block which is used in solution of many different problems. In cases when dimensionality of a problem exceeds two, a generalization of a singular value decomposition – tensor decompositions – are used ...
Pavel Iljin, Tatiana Samoilova
doaj +1 more source
Energy-Based Adaptive CUR Matrix Decomposition
IEEE Access, 2023 CUR decompositions are interpretable data analysis tools that express a data matrix in terms of a small number of actual columns and/or actual rows of the data matrix.
Liwen Xu, Xuejiao Zhao, Yongxia Zhang
doaj +1 more source
Prime decomposition of quadratic matrix polynomials
AIMS Mathematics, 2021 We study the prime decomposition of a quadratic monic matrix polynomial. From the prime decomposition of a quadratic matrix polynomial, we obtain a formula of the general solution to the corresponding second-order differential equation.
Yunbo Tian, Sheng Chen
doaj +1 more source
Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions [PDF]
, 2010 Low-rank matrix approximations, such as the truncated singular value decomposition and the rank-revealing QR decomposition, play a central role in data analysis and scientific computing.
Halko, Nathan +2 more
core +6 more sources
Materials & Design, 2022 Microstructure evolution, phase determination, phase decomposition and transition of mechanically alloyed Al0.8Co0.5Cr1.5CuFeNi during 950–1150 ℃ high temperature sintering, and the effect of sintered microstructures on mechanical properties were ...
Minjie Huang +4 more
doaj +1 more source
Decomposition of Matrix under Neutrosophic Environment [PDF]
Neutrosophic Sets and Systems, 2019 Matrices help for the effective representation of systems of linear equations and analyzing any sort of data. The decomposition of any matrix allows for the efficient implementation of matrix-based algorithms.
Muhammad Kashif +3 more
doaj +1 more source
A New Method of Kronecker Product Decomposition
Journal of Mathematics, 2023 Kronecker product decomposition is often applied in various fields such as particle physics, signal processing, image processing, semidefinite programming, quantum computing, and matrix time series analysis.
Yi Wu
doaj +1 more source
Scientific Reports, 2023 Because the traditional Cholesky decomposition algorithm still has some problems such as computational complexity and scattered structure among matrices when solving the GNSS ambiguity, it is the key problem to further improve the computational ...
Yingxiang Jiao +5 more
doaj +1 more source
On decomposition of k-tridiagonal ℓ-Toeplitz matrices and its applications
Special Matrices, 2015 We consider a k-tridiagonal ℓ-Toeplitz matrix as one of generalizations of a tridiagonal Toeplitz matrix. In the present paper, we provide a decomposition of the matrix under a certain condition.
Ohashi A., Sogabe T., Usuda T.S.
doaj +1 more source