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Listar por palabra clave "Independent component analysis (ICA)"

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Listar por palabra clave "Independent component analysis (ICA)"

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    Analysis of the effect of Action Observation and Motor Imagery on brain connectivity 
    Navarro Piles, Hugo (Universitat Politècnica de València, 2023-09-22)
    [ES] El objetivo principal de este estudio es investigar la conectividad cerebral durante dos condiciones diferentes: Tarea de Observación de la Acción (TOA) e Imaginería Motora (IM), utilizando la electroencefalografía ...
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    Generalized matched subspace filter for dependent noise based on ICA 
    Moragues Escrivá, Jorge; Vergara Domínguez, Luís; Gosálbez Castillo, Jorge (Institute of Electrical and Electronics Engineers (IEEE), 2011-07)
    We propose a generalization of the matched subspace filter for the detection of unknown signals in a background of non-Gaussian and nonindependent noise. The generalization is based on a modification of the Rao test by ...
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    Independent Component Analysis: Blind Source Separation 
    Boluda Burguete, Vicente (Universitat Politècnica de València, 2015-11-12)
    Independent Component Analysis (ICA) is a technique used since middle 80s, and due to all its applications, it has been a common research topic. Simplifying the concept, with the ICA technique we can separate multivariate ...
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    Nuevas contribuciones a la teoría y aplicación del procesado de señal sobre grafos 
    Belda Valls, Jordi (Universitat Politècnica de València, 2023-01-16)
    [ES] El procesado de señal sobre grafos es un campo emergente de técnicas que combinan conceptos de dos áreas muy consolidadas: el procesado de señal y la teoría de grafos. Desde la perspectiva del procesado de señal puede ...
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    Probabilistic Distance for Mixtures of Independent Component Analyzers 
    Safont Armero, Gonzalo; Salazar Afanador, Addisson; Vergara Domínguez, Luís; Gomez, Enriqueta; Villanueva, Vicente (Institute of Electrical and Electronics Engineers, 2018)
    [EN] Independent component analysis (ICA) is a blind source separation technique where data are modeled as linear combinations of several independent non-Gaussian sources. The independence and linear restrictions are relaxed ...