Inversion of Vandermonde matrices via synthetic division formulation

Vandermonde matrices are fundamental in applied mathematics, natural sciences, and engineering. The inverse form of the Vandermonde matrix (V) is one of its most important characteristics. The purpose of this paper is to develop an algorithm for the inverse of Vandermonde matrix, V-1 in the Python p...

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Published in:AIP Conference Proceedings
Main Author: Ahmad S.N.; Kadir N.K.I.A.; Nazri M.A.W.; Razali W.M.S.
Format: Conference paper
Language:English
Published: American Institute of Physics 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202643290&doi=10.1063%2f5.0224748&partnerID=40&md5=7b083ee065b593bc7c302a818a903f8f
id 2-s2.0-85202643290
spelling 2-s2.0-85202643290
Ahmad S.N.; Kadir N.K.I.A.; Nazri M.A.W.; Razali W.M.S.
Inversion of Vandermonde matrices via synthetic division formulation
2024
AIP Conference Proceedings
3189
1
10.1063/5.0224748
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202643290&doi=10.1063%2f5.0224748&partnerID=40&md5=7b083ee065b593bc7c302a818a903f8f
Vandermonde matrices are fundamental in applied mathematics, natural sciences, and engineering. The inverse form of the Vandermonde matrix (V) is one of its most important characteristics. The purpose of this paper is to develop an algorithm for the inverse of Vandermonde matrix, V-1 in the Python programming language using the Synthetic Division method. To compute the elements of V-1, the Synthetic Division uses arithmetic operations, multiplications, and additions. Consequently, inverse matrix computations require less time compared to a method that involved the multiplication of two matrices. In addition, the efficiency and time required to compute V-1 using Synthetic Division versus the numpy.linalg.inv() function in the Python NumPy module are compared. The study found that the NumPy inverse function demonstrated that the time computation of inverse matrices is consistent, except for certain sizes. In contrast, the Synthetic Division algorithm appears consistent regardless of matrix size. Therefore, Synthetic Division is an effective and efficient method for computing V-1. © 2024 Author(s).
American Institute of Physics
0094243X
English
Conference paper

author Ahmad S.N.; Kadir N.K.I.A.; Nazri M.A.W.; Razali W.M.S.
spellingShingle Ahmad S.N.; Kadir N.K.I.A.; Nazri M.A.W.; Razali W.M.S.
Inversion of Vandermonde matrices via synthetic division formulation
author_facet Ahmad S.N.; Kadir N.K.I.A.; Nazri M.A.W.; Razali W.M.S.
author_sort Ahmad S.N.; Kadir N.K.I.A.; Nazri M.A.W.; Razali W.M.S.
title Inversion of Vandermonde matrices via synthetic division formulation
title_short Inversion of Vandermonde matrices via synthetic division formulation
title_full Inversion of Vandermonde matrices via synthetic division formulation
title_fullStr Inversion of Vandermonde matrices via synthetic division formulation
title_full_unstemmed Inversion of Vandermonde matrices via synthetic division formulation
title_sort Inversion of Vandermonde matrices via synthetic division formulation
publishDate 2024
container_title AIP Conference Proceedings
container_volume 3189
container_issue 1
doi_str_mv 10.1063/5.0224748
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202643290&doi=10.1063%2f5.0224748&partnerID=40&md5=7b083ee065b593bc7c302a818a903f8f
description Vandermonde matrices are fundamental in applied mathematics, natural sciences, and engineering. The inverse form of the Vandermonde matrix (V) is one of its most important characteristics. The purpose of this paper is to develop an algorithm for the inverse of Vandermonde matrix, V-1 in the Python programming language using the Synthetic Division method. To compute the elements of V-1, the Synthetic Division uses arithmetic operations, multiplications, and additions. Consequently, inverse matrix computations require less time compared to a method that involved the multiplication of two matrices. In addition, the efficiency and time required to compute V-1 using Synthetic Division versus the numpy.linalg.inv() function in the Python NumPy module are compared. The study found that the NumPy inverse function demonstrated that the time computation of inverse matrices is consistent, except for certain sizes. In contrast, the Synthetic Division algorithm appears consistent regardless of matrix size. Therefore, Synthetic Division is an effective and efficient method for computing V-1. © 2024 Author(s).
publisher American Institute of Physics
issn 0094243X
language English
format Conference paper
accesstype
record_format scopus
collection Scopus
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