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3 Result(s)

within Jason A. Palmer Remove this filter Coding and Information Theory Remove this filter

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  1. No Access

    Chapter and Conference Paper

    Probabilistic Formulation of Independent Vector Analysis Using Complex Gaussian Scale Mixtures

    We propose a probabilistic model for the Independent Vector Analysis approach to blind deconvolution and derive an asymptotic Newton method to estimate the model by Maximum Likelihood.

    Jason A. Palmer, Ken Kreutz-Delgado… in Independent Component Analysis and Signal … (2009)

  2. No Access

    Chapter and Conference Paper

    Modeling and Estimation of Dependent Subspaces with Non-radially Symmetric and Skewed Densities

    We extend the Gaussian scale mixture model of dependent subspace source densities to include non-radially symmetric densities using Generalized Gaussian random variables linked by a common variance. We also in...

    Jason A. Palmer, Ken Kreutz-Delgado… in Independent Component Analysis and Signal … (2007)

  3. No Access

    Chapter and Conference Paper

    Super-Gaussian Mixture Source Model for ICA

    We propose an extension of the mixture of factor (or independent component) analyzers model to include strongly super-gaussian mixture source densities. This allows greater economy in representation of densiti...

    Jason A. Palmer, Kenneth Kreutz-Delgado… in Independent Component Analysis and Blind S… (2006)