Mostrar el registro sencillo del ítem

REDUNDANCY IN GAUSSIAN RANDOM FIELDS

hal.structure.identifierCB - Centre Borelli - UMR 9010 [CB]
dc.contributor.authorDE BORTOLI, Valentin
hal.structure.identifierCB - Centre Borelli - UMR 9010 [CB]
dc.contributor.authorDESOLNEUX, Agnès
hal.structure.identifierInstitut Denis Poisson [IDP]
dc.contributor.authorGALERNE, Bruno
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorLECLAIRE, Arthur
dc.date.accessioned2024-04-04T03:04:05Z
dc.date.available2024-04-04T03:04:05Z
dc.date.issued2020
dc.identifier.issn1292-8100
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/193118
dc.description.abstractEnWe introduce and study a notion of spatial redundancy in Gaussian random fields. we define similarity functions with some properties and give insight about their statistical properties in the context of image processing. We compute these similarity functions on local windows in random fields defined over discrete or continuous domains. We give explicit asymptotic Gaussian expressions for the distribution of similarity function random variables when computed over Gaussian random fields and illustrate the weaknesses of such Gaussian approximations by showing that the approximated probability of rare events is not precise enough, even for large windows. In the special case of the squared L 2 norm, non-asymptotic expressions are derived in both discrete and continuous periodic settings. A fast and accurate approximation is introduced using eigenvalues projection and moment methods.
dc.language.isoen
dc.publisherEDP Sciences
dc.subject.enRandom fields
dc.subject.enspatial redundancy
dc.subject.encentral limit theorem
dc.subject.enlaw of large numbers
dc.subject.eneigenvalues approximation
dc.subject.enmoment methods
dc.title.enREDUNDANCY IN GAUSSIAN RANDOM FIELDS
dc.typeArticle de revue
dc.identifier.doi10.1051/ps/2020010
dc.subject.halMathématiques [math]/Probabilités [math.PR]
dc.subject.halMathématiques [math]/Statistiques [math.ST]
bordeaux.journalESAIM: Probability and Statistics
bordeaux.pagepp. 627-660
bordeaux.volumeVol. 24
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01931737
hal.version2
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01931737v2
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=ESAIM:%20Probability%20and%20Statistics&rft.date=2020&rft.volume=Vol.%2024&rft.spage=pp.%20627-660&rft.epage=pp.%20627-660&rft.eissn=1292-8100&rft.issn=1292-8100&rft.au=DE%20BORTOLI,%20Valentin&DESOLNEUX,%20Agn%C3%A8s&GALERNE,%20Bruno&LECLAIRE,%20Arthur&rft.genre=article


Archivos en el ítem

ArchivosTamañoFormatoVer

No hay archivos asociados a este ítem.

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem