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Nonlinear estimators from ICA mixture models

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Nonlinear estimators from ICA mixture models

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Safont Armero, G.; Salazar Afanador, A.; Vergara Domínguez, L.; Rodriguez Martinez, A. (2019). Nonlinear estimators from ICA mixture models. Signal Processing. 155:281-286. https://doi.org/10.1016/j.sigpro.2018.10.003

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/157360

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Title: Nonlinear estimators from ICA mixture models
Author: Safont Armero, Gonzalo Salazar Afanador, Addisson Vergara Domínguez, Luís RODRIGUEZ MARTINEZ, ALBERTO
UPV Unit: Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia
Issued date:
Abstract:
[EN] Independent Component Analyzers Mixture Models (ICAMM) are versatile and general models for a large variety of probability density functions. In this paper we assume ICAMM to derive new MAP and LMSE estimators. The ...[+]
Subjects: ICA , Nonlinear estimators , LMSE , MAP , EEG reconstruction , Non-Gaussian mixtures
Copyrigths: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Source:
Signal Processing. (issn: 0165-1684 )
DOI: 10.1016/j.sigpro.2018.10.003
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.sigpro.2018.10.003
Project ID:
info:eu-repo/grantAgreement/MINECO//TEC2014-58438-R/ES/PROCESADO DE SEÑAL SOBRE GRAFOS PARA SISTEMAS CLASIFICADORES: APLICACION EN SALUD, ENERGIA Y SEGURIDAD/
info:eu-repo/grantAgreement/GVA//PROMETEOII%2F2014%2F032/ES/TÉCNICAS AVANZADAS DE FUSIÓN EN TRATAMIENTO DE SEÑALES/
Description: "NOTICE: this is the author's version of a work that was accepted for publication in Signal Processing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Signal Processing, 155, (2019) https://doi.org/10.1016/j.sigpro.2018.10.003"
Thanks:
This work was supported by Spanish Administration (Ministerio de Economia y Competitividad) and European Union (FEDER) under grant TEC2014-58438-R, and Generalitat Valenciana under grant PROMETEO II/2014/032.
Type: Artículo

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