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Solution of underdetermined systems of equations with gridded a priori constraints
The TOPINV, Topological Inversion algorithm (or TGS, Topological Grid Search) initially developed for the inversion of highly non-linear redundant systems of equations, can solve a wide range of underdetermined systems of non-linear equations. This approach is a generalization of a previous conclusi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4320199/ https://www.ncbi.nlm.nih.gov/pubmed/25674445 http://dx.doi.org/10.1186/2193-1801-3-145 |
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author | Stiros, Stathis C Saltogianni, Vasso |
author_facet | Stiros, Stathis C Saltogianni, Vasso |
author_sort | Stiros, Stathis C |
collection | PubMed |
description | The TOPINV, Topological Inversion algorithm (or TGS, Topological Grid Search) initially developed for the inversion of highly non-linear redundant systems of equations, can solve a wide range of underdetermined systems of non-linear equations. This approach is a generalization of a previous conclusion that this algorithm can be used for the solution of certain integer ambiguity problems in Geodesy. The overall approach is based on additional (a priori) information for the unknown variables. In the past, such information was used either to linearize equations around approximate solutions, or to expand systems of observation equations solved on the basis of generalized inverses. In the proposed algorithm, the a priori additional information is used in a third way, as topological constraints to the unknown n variables, leading to an R(n) grid containing an approximation of the real solution. The TOPINV algorithm does not focus on point-solutions, but exploits the structural and topological constraints in each system of underdetermined equations in order to identify an optimal closed space in the R(n) containing the real solution. The centre of gravity of the grid points defining this space corresponds to global, minimum-norm solutions. The rationale and validity of the overall approach are demonstrated on the basis of examples and case studies, including fault modelling, in comparison with SVD solutions and true (reference) values, in an accuracy-oriented approach. |
format | Online Article Text |
id | pubmed-4320199 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-43201992015-02-11 Solution of underdetermined systems of equations with gridded a priori constraints Stiros, Stathis C Saltogianni, Vasso Springerplus Research The TOPINV, Topological Inversion algorithm (or TGS, Topological Grid Search) initially developed for the inversion of highly non-linear redundant systems of equations, can solve a wide range of underdetermined systems of non-linear equations. This approach is a generalization of a previous conclusion that this algorithm can be used for the solution of certain integer ambiguity problems in Geodesy. The overall approach is based on additional (a priori) information for the unknown variables. In the past, such information was used either to linearize equations around approximate solutions, or to expand systems of observation equations solved on the basis of generalized inverses. In the proposed algorithm, the a priori additional information is used in a third way, as topological constraints to the unknown n variables, leading to an R(n) grid containing an approximation of the real solution. The TOPINV algorithm does not focus on point-solutions, but exploits the structural and topological constraints in each system of underdetermined equations in order to identify an optimal closed space in the R(n) containing the real solution. The centre of gravity of the grid points defining this space corresponds to global, minimum-norm solutions. The rationale and validity of the overall approach are demonstrated on the basis of examples and case studies, including fault modelling, in comparison with SVD solutions and true (reference) values, in an accuracy-oriented approach. Springer International Publishing 2014-03-17 /pmc/articles/PMC4320199/ /pubmed/25674445 http://dx.doi.org/10.1186/2193-1801-3-145 Text en © Stiros and Saltogianni; licensee Springer. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. |
spellingShingle | Research Stiros, Stathis C Saltogianni, Vasso Solution of underdetermined systems of equations with gridded a priori constraints |
title | Solution of underdetermined systems of equations with gridded a priori constraints |
title_full | Solution of underdetermined systems of equations with gridded a priori constraints |
title_fullStr | Solution of underdetermined systems of equations with gridded a priori constraints |
title_full_unstemmed | Solution of underdetermined systems of equations with gridded a priori constraints |
title_short | Solution of underdetermined systems of equations with gridded a priori constraints |
title_sort | solution of underdetermined systems of equations with gridded a priori constraints |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4320199/ https://www.ncbi.nlm.nih.gov/pubmed/25674445 http://dx.doi.org/10.1186/2193-1801-3-145 |
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