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Multichannel dynamic modeling of non-Gaussian mixtures

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Multichannel dynamic modeling of non-Gaussian mixtures

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Safont Armero, G.; Salazar Afanador, A.; Vergara Domínguez, L.; Gomez, E.; Villanueva, V. (2019). Multichannel dynamic modeling of non-Gaussian mixtures. Pattern Recognition. 93:312-323. https://doi.org/10.1016/j.patcog.2019.04.022

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/156422

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Title: Multichannel dynamic modeling of non-Gaussian mixtures
Author: Safont Armero, Gonzalo Salazar Afanador, Addisson Vergara Domínguez, Luís Gomez, Enriqueta Villanueva, Vicente
UPV Unit: Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia
Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Issued date:
Abstract:
[EN] This paper presents a novel method that combines coupled hidden Markov models (HMM) and non Gaussian mixture models based on independent component analyzer mixture models (ICAMM). The proposed method models the joint ...[+]
Subjects: Dynamic modeling , Non-Gaussian mixtures , ICA , HMM , EEG
Copyrigths: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Source:
Pattern Recognition. (issn: 0031-3203 )
DOI: 10.1016/j.patcog.2019.04.022
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.patcog.2019.04.022
Project ID:
MINECO/TEC2017-84743-P
info:eu-repo/grantAgreement/MINECO//TEC2014-58438-R/ES/PROCESADO DE SEÑAL SOBRE GRAFOS PARA SISTEMAS CLASIFICADORES: APLICACION EN SALUD, ENERGIA Y SEGURIDAD/
Thanks:
This work was supported by Spanish Administration (Ministerio de Economia y Competitividad) and European Union (FEDER) under grants TEC2014-58438-R and TEC2017-84743-P.
Type: Artículo

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