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Dependent Component Analysis

  1. Research

    Independent vector analysis using subband and subspace nonlinearity

    Independent vector analysis (IVA) is a recently proposed technique, an application of which is to solve the frequency domain blind source separation problem. Compared with the traditional complex-valued indepe...

    Yueyue Na, Jian Yu and Bianfang Chai

    EURASIP Journal on Advances in Signal Processing 2013 2013:74

    Published on: 10 April 2013

  2. Research

    Separation of phase-locked sources in pseudo-real MEG data

    This article addresses the blind separation of linear mixtures of synchronous signals (i.e., signals with locked phases), which is a relevant problem, e.g., in the analysis of electrophysiological signals of t...

    Miguel Almeida, José Bioucas-Dias and Ricardo Vigário

    EURASIP Journal on Advances in Signal Processing 2013 2013:32

    Published on: 22 February 2013

  3. Research

    Dependent Gaussian mixture models for source separation

    Source separation is a common task in signal processing and is often analogous to factor analysis. In this study, we look at a factor analysis model for source separation of multi-spectral image data where pri...

    Alicia Quirós and Simon P Wilson

    EURASIP Journal on Advances in Signal Processing 2012 2012:239

    Published on: 16 November 2012