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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VSB-Technical University of Ostrava
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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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1716828144832348160 |