Application of Matrix Decompositions for Matrix Canonization
- Authors: Volkov V.G.1, Dem’yanov D.N.1
-
Affiliations:
- Naberezhnye Chelny Institute, Branch of Kazan Federal University
- Issue: Vol 59, No 11 (2019)
- Pages: 1759-1770
- Section: Article
- URL: https://journal-vniispk.ru/0965-5425/article/view/180872
- DOI: https://doi.org/10.1134/S0965542519110149
- ID: 180872
Cite item
Abstract
The problem of solving overdetermined, underdetermined, singular, or ill conditioned SLAEs using matrix canonization is considered. A modification of an existing canonization algorithm based on matrix decomposition is proposed. Formulas using LU decomposition, QR decomposition, LQ decomposition, or singular value decomposition, depending on the properties of the given matrix, are obtained. A method for evaluating the condition number of the canonization problem is proposed. It is based on computing the norm of the matrices obtained as a result of canonization; this method does not require the original matrix to be inverted. A general step-by-step matrix canonization algorithm is described and implemented in MATLAB. The implementation is tested on a set of 100 000 randomly generated matrices. The testing results confirmed the validity and efficiency of the proposed algorithm.
About the authors
V. G. Volkov
Naberezhnye Chelny Institute, Branch of Kazan Federal University
Author for correspondence.
Email: vgvolkov93@mail.ru
Russian Federation, Naberezhnye Chelny, 423812
D. N. Dem’yanov
Naberezhnye Chelny Institute, Branch of Kazan Federal University
Email: vgvolkov93@mail.ru
Russian Federation, Naberezhnye Chelny, 423812
Supplementary files
