Comparison descent directions for Conjugate Gradient Method
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| Format: | Artículo científico |
| Langue: | en |
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Universidad Tecnológica de Pereira
2021
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| _version_ | 1866814518217146368 |
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| author | Fernando Mesa |
| author_facet | Fernando Mesa |
| contents | Comparison descent directions for Conjugate Gradient Method Fernando Mesa Diana Marcela Devia Narváez German Correa Vélez Ingeniería descent gradient solution iteration minimization In the following manuscript we will show as a starting point a theoretical analysis of the gradient method, known as one of the first descent methods, and from this we will identify the strength of the conjugate gradient methods. Taking an objective function, we will determine the values that optimize it by means of different methods, indicating the differences of geometric type that these have. Different systems will be used, in order to serve as a test, obtaining their solution in each case and finding the speed at which they converge in accordance with the conjugate gradient methods proposed by Hestenes-Stiefel and Fletcher-Reeves. 2021 artículo científico 0122-1701 https://www.redalyc.org/articulo.oa?id=84969892012 https://www.redalyc.org/journal/849/84969892012/ https://www.redalyc.org/journal/849/84969892012/html/ https://www.redalyc.org/journal/849/84969892012/84969892012.epub https://www.redalyc.org/journal/849/84969892012/movil https://doi.org/10.22517/23447214.24893 en http://www.redalyc.org/revista.oa?id=849 Scientia Et Technica application/pdf Universidad Tecnológica de Pereira Scientia Et Technica (Colombia) Num.4 Vol.26 |
| format | Artículo científico |
| id | redalyc_84969892012 |
| language | en |
| publishDate | 2021 |
| publisher | Universidad Tecnológica de Pereira |
| spellingShingle | Comparison descent directions for Conjugate Gradient Method Fernando Mesa Ingeniería descent gradient solution iteration minimization Comparison descent directions for Conjugate Gradient Method Fernando Mesa Diana Marcela Devia Narváez German Correa Vélez Ingeniería descent gradient solution iteration minimization In the following manuscript we will show as a starting point a theoretical analysis of the gradient method, known as one of the first descent methods, and from this we will identify the strength of the conjugate gradient methods. Taking an objective function, we will determine the values that optimize it by means of different methods, indicating the differences of geometric type that these have. Different systems will be used, in order to serve as a test, obtaining their solution in each case and finding the speed at which they converge in accordance with the conjugate gradient methods proposed by Hestenes-Stiefel and Fletcher-Reeves. 2021 artículo científico 0122-1701 https://www.redalyc.org/articulo.oa?id=84969892012 https://www.redalyc.org/journal/849/84969892012/ https://www.redalyc.org/journal/849/84969892012/html/ https://www.redalyc.org/journal/849/84969892012/84969892012.epub https://www.redalyc.org/journal/849/84969892012/movil https://doi.org/10.22517/23447214.24893 en http://www.redalyc.org/revista.oa?id=849 Scientia Et Technica application/pdf Universidad Tecnológica de Pereira Scientia Et Technica (Colombia) Num.4 Vol.26 |
| title | Comparison descent directions for Conjugate Gradient Method |
| topic | Ingeniería descent gradient solution iteration minimization |
| url | https://www.redalyc.org/articulo.oa?id=84969892012 https://www.redalyc.org/journal/849/84969892012/ https://www.redalyc.org/journal/849/84969892012/html/ https://www.redalyc.org/journal/849/84969892012/84969892012.epub https://www.redalyc.org/journal/849/84969892012/movil https://doi.org/10.22517/23447214.24893 |