Analysis of Fixing Nodes Used in Generalized Inverse Computation

In various fields of numerical mathematics, there arises the need to compute a generalized inverse of a symmetric positive semidefinite matrix, for example in the solution of contact problems. Systems with semidefinite matrices can be solved by standard direct methods for the solution of systems wit...

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Main Author: Pavla Hruskova
Format: Article
Language:English
Published: VSB-Technical University of Ostrava 2014-01-01
Series:Advances in Electrical and Electronic Engineering
Subjects:
Online Access:http://advances.utc.sk/index.php/AEEE/article/view/1020
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spelling doaj-ed583d5484d54fdb9fb4219eb0b8a6112021-10-11T08:03:03ZengVSB-Technical University of OstravaAdvances in Electrical and Electronic Engineering1336-13761804-31192014-01-0112212313010.15598/aeee.v12i2.1020653Analysis of Fixing Nodes Used in Generalized Inverse ComputationPavla Hruskova0Department of applied mathematics, Faculty of Electrical Engineering and Computer Science, VSB-Technical University OstravaIn various fields of numerical mathematics, there arises the need to compute a generalized inverse of a symmetric positive semidefinite matrix, for example in the solution of contact problems. Systems with semidefinite matrices can be solved by standard direct methods for the solution of systems with positive definite matrices adapted to the solution of systems with only positive semidefinite matrix. One of the possibilities is a modification of Cholesky decomposition using so called fixing nodes, which is presented in this paper with particular emphasise on proper definition of fixing nodes. The generalised inverse algorithm consisting in Cholesky decomposition with usage of fixing nodes is adopted from paper [1]. In [1], authors choose the fixing nodes using Perron vector of an adjacency matrix of the graph which is only a sub-optimal choice. Their choice is discussed in this paper together with other possible candidates on fixing node. Several numerical experiments including all candidates have been done. Based on these results, it turns out that using eigenvectors of Laplacian matrix provides better choice of fixing node than using Perron vector.http://advances.utc.sk/index.php/AEEE/article/view/1020cholesky decompositionfixing nodesgeneralised inverselaplacian matrixspectral graph theorystiffness matrix.
collection DOAJ
language English
format Article
sources DOAJ
author Pavla Hruskova
spellingShingle Pavla Hruskova
Analysis of Fixing Nodes Used in Generalized Inverse Computation
Advances in Electrical and Electronic Engineering
cholesky decomposition
fixing nodes
generalised inverse
laplacian matrix
spectral graph theory
stiffness matrix.
author_facet Pavla Hruskova
author_sort Pavla Hruskova
title Analysis of Fixing Nodes Used in Generalized Inverse Computation
title_short Analysis of Fixing Nodes Used in Generalized Inverse Computation
title_full Analysis of Fixing Nodes Used in Generalized Inverse Computation
title_fullStr Analysis of Fixing Nodes Used in Generalized Inverse Computation
title_full_unstemmed Analysis of Fixing Nodes Used in Generalized Inverse Computation
title_sort analysis of fixing nodes used in generalized inverse computation
publisher VSB-Technical University of Ostrava
series Advances in Electrical and Electronic Engineering
issn 1336-1376
1804-3119
publishDate 2014-01-01
description In various fields of numerical mathematics, there arises the need to compute a generalized inverse of a symmetric positive semidefinite matrix, for example in the solution of contact problems. Systems with semidefinite matrices can be solved by standard direct methods for the solution of systems with positive definite matrices adapted to the solution of systems with only positive semidefinite matrix. One of the possibilities is a modification of Cholesky decomposition using so called fixing nodes, which is presented in this paper with particular emphasise on proper definition of fixing nodes. The generalised inverse algorithm consisting in Cholesky decomposition with usage of fixing nodes is adopted from paper [1]. In [1], authors choose the fixing nodes using Perron vector of an adjacency matrix of the graph which is only a sub-optimal choice. Their choice is discussed in this paper together with other possible candidates on fixing node. Several numerical experiments including all candidates have been done. Based on these results, it turns out that using eigenvectors of Laplacian matrix provides better choice of fixing node than using Perron vector.
topic cholesky decomposition
fixing nodes
generalised inverse
laplacian matrix
spectral graph theory
stiffness matrix.
url http://advances.utc.sk/index.php/AEEE/article/view/1020
work_keys_str_mv AT pavlahruskova analysisoffixingnodesusedingeneralizedinversecomputation
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