Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Lucini, María Magdalena"'
Model uncertainty estimation using the expectation maximization algorithm and a particle flow filter
Model error covariances play a central role in the performance of data assimilation methods applied to nonlinear state-space models. However, these covariances are largely unknown in most of the applications. A misspecification of the model error cov
Externí odkaz:
http://arxiv.org/abs/1911.01511
In this paper we analyze several strategies for the estimation of the roughness parameter of the $\mathcal G_I^0$ distribution. It has been shown that this distribution is able to characterize a large number of targets in monopolarized SAR imagery, d
Externí odkaz:
http://arxiv.org/abs/1408.0177
Autor:
Pulido, Manuel Arturo, Scheffler, Guillermo, Ruiz, Juan José, Lucini, María Magdalena, Tandeo, Pierre
Publikováno v:
Quarterly Journal of the Royal Meteorological Society, 2016, vol. 142, p. 2974–2984.
Repositorio Institucional de la Universidad Nacional del Nordeste (UNNE)
Universidad Nacional del Nordeste
instacron:UNNE
Repositorio Institucional de la Universidad Nacional del Nordeste (UNNE)
Universidad Nacional del Nordeste
instacron:UNNE
Fil: Pulido, Manuel Arturo. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura; Argentina. Fil: Pulido, Manuel Arturo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Franco-Argentino de Es
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3056::9a5b6ab1044ab641c43239abdb3ee277
http://repositorio.unne.edu.ar/handle/123456789/30326
http://repositorio.unne.edu.ar/handle/123456789/30326
Publikováno v:
Repositorio Digital Universitario (UNC)
Universidad Nacional de Córdoba
instacron:UNC
Universidad Nacional de Córdoba
instacron:UNC
Statistical properties of image data are of paramount importance in the design of pattern recognition technics and the interpretation of their outputs. Image simulation allows quantification of method?s error and accuracy. In the case of SAR images,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3056::6df2b05dc6245a87b894f801af6c16d0
Remote sensing data present peculiar features and characteristics that may make their statistical processing and analysis a difficult task. Among them, it can be mentioned the volume of data involved, the redundancy, the presence of unexpected values
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3498::a321ea0506fa69c9b247fda2ad6cf9d0
https://link.springer.com/chapter/10.1007/978-3-642-02611-9_13
https://link.springer.com/chapter/10.1007/978-3-642-02611-9_13
Fil: Siqueira, Arminda Lucia. Universidade Federal de Minas Gerais; Brasil Fil: Whitehead, Anne. University of Reading; Reino Unido Fil: Todd, Susan. University of Reading; Reino Unido Fil: Lucini, María Magdalena. Consejo Nacional de Investigacione
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3498::381cedd1d7bcfb0c35daedc4da9f7736
Wiley Online Library
Wiley Online Library
Publikováno v:
EURASIP Journal on Advances in Signal Processing. 2002(1):105-114
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::9c89f47f46e4a4bf028af0cbc739a442
