Recursive approach for constructing the q = 1/2 maximum entropy distribution from redundant data
A recursive approach for computing the q = 1/2 nonextensive maximum entropy distribution of the previously introduced formalism for data subset selection is proposed. Such an approach is based on an iterative biorthogonalization technique, which allows for the incorporation of the Lagrange multiplie...
Guardado en:
| Autores principales: | , |
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| Formato: | Articulo |
| Lenguaje: | Inglés |
| Publicado: |
2002
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/125907 |
| Aporte de: |
| id |
I19-R120-10915-125907 |
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| record_format |
dspace |
| institution |
Universidad Nacional de La Plata |
| institution_str |
I-19 |
| repository_str |
R-120 |
| collection |
SEDICI (UNLP) |
| language |
Inglés |
| topic |
Física Joint entropy Algorithm Mathematical optimization Mathematics Joint quantum entropy Binary entropy function Maximum entropy thermodynamics Maximum entropy probability distribution Lagrange multiplier Maximum entropy spectral estimation Principle of maximum entropy |
| spellingShingle |
Física Joint entropy Algorithm Mathematical optimization Mathematics Joint quantum entropy Binary entropy function Maximum entropy thermodynamics Maximum entropy probability distribution Lagrange multiplier Maximum entropy spectral estimation Principle of maximum entropy Rebollo Neira, Laura Plastino, Ángel Luis Recursive approach for constructing the q = 1/2 maximum entropy distribution from redundant data |
| topic_facet |
Física Joint entropy Algorithm Mathematical optimization Mathematics Joint quantum entropy Binary entropy function Maximum entropy thermodynamics Maximum entropy probability distribution Lagrange multiplier Maximum entropy spectral estimation Principle of maximum entropy |
| description |
A recursive approach for computing the q = 1/2 nonextensive maximum entropy distribution of the previously introduced formalism for data subset selection is proposed. Such an approach is based on an iterative biorthogonalization technique, which allows for the incorporation of the Lagrange multipliers that determine the distribution to the workings of the algorithm devised for selecting relevant data subsets. This technique circumvents the necessity of inverting operators and yields a recursive procedure to appropriately modify the Lagrange multipliers so as to account for each new constraint. |
| format |
Articulo Articulo |
| author |
Rebollo Neira, Laura Plastino, Ángel Luis |
| author_facet |
Rebollo Neira, Laura Plastino, Ángel Luis |
| author_sort |
Rebollo Neira, Laura |
| title |
Recursive approach for constructing the q = 1/2 maximum entropy distribution from redundant data |
| title_short |
Recursive approach for constructing the q = 1/2 maximum entropy distribution from redundant data |
| title_full |
Recursive approach for constructing the q = 1/2 maximum entropy distribution from redundant data |
| title_fullStr |
Recursive approach for constructing the q = 1/2 maximum entropy distribution from redundant data |
| title_full_unstemmed |
Recursive approach for constructing the q = 1/2 maximum entropy distribution from redundant data |
| title_sort |
recursive approach for constructing the q = 1/2 maximum entropy distribution from redundant data |
| publishDate |
2002 |
| url |
http://sedici.unlp.edu.ar/handle/10915/125907 |
| work_keys_str_mv |
AT rebolloneiralaura recursiveapproachforconstructingtheq12maximumentropydistributionfromredundantdata AT plastinoangelluis recursiveapproachforconstructingtheq12maximumentropydistributionfromredundantdata |
| bdutipo_str |
Repositorios |
| _version_ |
1764820452483530754 |