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pro vyhledávání: '"João V. T. de Lima"'
Autor:
Gustavo Z. dos Santos Lima, João V. T. de Lima, João M. de Araújo, Gilberto Corso, Sérgio Luiz E. F. da Silva
Publikováno v:
PLoS ONE, Vol 18, Iss 3 (2023)
The conventional approach to data-driven inversion framework is based on Gaussian statistics that presents serious difficulties, especially in the presence of outliers in the measurements. In this work, we present maximum likelihood estimators associ
Externí odkaz:
https://doaj.org/article/d709c2b6ecfa4eada46e467c67741eca
Autor:
Gustavo Z. dos Santos Lima, João V. T. de Lima, João M. de Araújo, Gilberto Corso, Sérgio Luiz E. F. da Silva
The conventional approach to data-driven inversion framework is based on Gaussian statistics that presents serious difficulties, especially in the presence of outliers in the measurements. In this work, we present maximum likelihood estimators associ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::92e2f80df01112089a377be36b213665
Autor:
Gilberto Corso, Sérgio Luiz E. F. da Silva, Gustavo Zampier dos Santos Lima, João V. T. de Lima, João M. de Araújo
Publikováno v:
The European Physical Journal Plus. 136
The problem of inferencing parameters of complex systems from measured data has been extensively studied based on the inverse problem theory. Classically, an inverse problem is formulated as an optimisation task in which the objective function is bas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::991b83f25b9847907125f59dcf95ab96
https://doi.org/10.1140/epjp/s13360-021-01274-6
https://doi.org/10.1140/epjp/s13360-021-01274-6