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Mixtures of independent component analyzers for EEG prediction

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Mixtures of independent component analyzers for EEG prediction

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Safont Armero, G.; Salazar Afanador, A.; Vergara Domínguez, L.; Gonzalez, A.; Vidal Maciá, AM. (2012). Mixtures of independent component analyzers for EEG prediction. En Green and smart technology with sensor applications. Springer Verlag (Germany). 338:328-335. doi:10.1007/978-3-642-35251-5_46

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/35381

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Title: Mixtures of independent component analyzers for EEG prediction
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia
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Abstract:
This paper presents a new application of independent component analysis mixture modeling (ICAMM) for prediction of electroencephalographic (EEG) signals. Demonstrations in prediction of missing EEG data in a working memory ...[+]
Subjects: Electroencefalogramas , ICA , Predicción , Tareas de memoria , EEG , Prediction , Working-memory task
Copyrigths: Reserva de todos los derechos
ISBN: 978-3-642-35250-8
Source:
Green and smart technology with sensor applications. (issn: 1865-0929 )
DOI: 10.1007/978-3-642-35251-5_46
Publisher:
Springer Verlag (Germany)
Publisher version: http://link.springer.com/chapter/10.1007%2F978-3-642-35251-5_46
Conference name: International Conferences, GST and SIA 2012
Conference place: Jeju Island, Korea
Conference date: November 28-December 2, 2012
Series: Communications in Computer and Information Science;338
Type: Capítulo de libro

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