An Overview Of Blind Source Separation Methods For Linear-quadratic And Post-nonlinear Mixtures

dc.creatorDeville
dc.creatorYannick; Duarte
dc.creatorLeonardo Tomazeli
dc.date2015
dc.date2016-06-07T13:22:56Z
dc.date2016-06-07T13:22:56Z
dc.date.accessioned2018-03-29T01:42:27Z
dc.date.available2018-03-29T01:42:27Z
dc.identifier978-3-319-22482-4; 978-3-319-22481-7
dc.identifierAn Overview Of Blind Source Separation Methods For Linear-quadratic And Post-nonlinear Mixtures. Springer-verlag Berlin, v. 9237, p. 155-167 2015.
dc.identifier0302-9743
dc.identifierWOS:000363785500018
dc.identifier10.1007/978-3-319-22482-4_18
dc.identifierhttp://link.springer.com/chapter/10.1007%2F978-3-319-22482-4_18
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/243282
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1306980
dc.descriptionWhereas most blind source separation (BSS) and blind mixture identification (BMI) investigations concern linear mixtures (instantaneous or not), various recent works extended BSS and BMI to nonlinear mixing models. They especially focused on two types of models, namely linear-quadratic ones (including their bilinear and quadratic versions, and some polynomial extensions) and post-nonlinear ones. These works are particularly motivated by the associated application fields, which include remote sensing, processing of scanned images (show-through effect) and design of smart chemical and gas sensor arrays. In this paper, we provide an overview of the above two types of mixing models and of the associated BSS and/or BMI methods and applications.
dc.description9237
dc.description
dc.description
dc.description155
dc.description167
dc.description
dc.description
dc.description
dc.languageen
dc.publisherSPRINGER-VERLAG BERLIN
dc.publisher
dc.publisherBERLIN
dc.relationLATENT VARIABLE ANALYSIS AND SIGNAL SEPARATION, LVA/ICA 2015
dc.rightsfechado
dc.sourceWOS
dc.subjectRecurrent Neural-network
dc.subjectHyperspectral Images
dc.subjectMaximum-likelihood
dc.subjectModel
dc.subjectAlgorithm
dc.subjectIca
dc.subjectIdentifiability
dc.subjectConfigurations
dc.subjectCompensation
dc.subjectInversion
dc.titleAn Overview Of Blind Source Separation Methods For Linear-quadratic And Post-nonlinear Mixtures
dc.typeActas de congresos


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