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Nonlinear prediction based on independent component analysis mixture modelling

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Nonlinear prediction based on independent component analysis mixture modelling

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Safont Armero, G.; Salazar Afanador, A.; Vergara Domínguez, L. (2011). Nonlinear prediction based on independent component analysis mixture modelling. Lecture Notes in Computer Science. 6691(1):508-515. doi:10.1007/978-3-642-21498-1_64

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/58589

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Title: Nonlinear prediction based on independent component analysis mixture modelling
Author: Safont Armero, Gonzalo Salazar Afanador, Addisson Vergara Domínguez, Luís
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 new algorithm for nonlinear prediction based on independent component analysis mixture modelling (ICAMM). The data are considered from several mutually-exclusive classes which are generated by ...[+]
Subjects: ICA , ICAMM , Kriging , Nonlinear prediction , Wiener structure , Algorithms , Forecasting , Mixtures , Neural networks , Time series , Independent component analysis
Copyrigths: Reserva de todos los derechos
Source:
Lecture Notes in Computer Science. (issn: 0302-9743 )
DOI: 10.1007/978-3-642-21498-1_64
Publisher:
Springer Verlag (Germany)
Publisher version: http://dx.doi.org/10.1007/978-3-642-21498-1_64
Thanks:
This work has been supported by the Generalitat Valenciana under grant PROMETEO/2010/040, and the Spanish Administration and the FEDER Programme of the European Union under grant TEC 2008-02975/TEC.
Type: Artículo

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