Independent Component Analysis and Signal Separation

8th International Conference, ICA 2009, Paraty, Brazil, March 15-18, 2009. Proceedings

ISBN: 978-3-642-00598-5 (Print) 978-3-642-00599-2 (Online)

Table of contents (97 chapters)

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  1. Front Matter

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  2. Theory

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      Pages 1-8

      Stationary Subspace Analysis

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      Pages 9-16

      Reference Based Contrast Functions in a Semi-blind Context

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      Pages 17-24

      On the Relationships between MMSE and Information-Theoretic-Based Blind Criterion for Minimum BER Filtering

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      Pages 25-33

      Blind Separation of Cyclostationary Signals

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      Pages 34-41

      A Novel Subspace Clustering Method for Dictionary Design

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      Pages 42-49

      Comparison of Two Main Approaches to Joint SVD

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      Pages 50-57

      Optimal Performance of Second-Order Multidimensional ICA

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      Pages 58-65

      Using Signal Invariants to Perform Nonlinear Blind Source Separation

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      Pages 66-73

      Bayesian Robust PCA for Incomplete Data

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      Pages 74-81

      Independent Component Analysis (ICA) Using Pearsonian Density Function

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      Pages 82-89

      An Analysis of Unsupervised Signal Processing Methods in the Context of Correlated Sources

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      Pages 90-97

      Probabilistic Formulation of Independent Vector Analysis Using Complex Gaussian Scale Mixtures

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      Pages 98-105

      Modeling the Short Time Fourier Transform Ratio and Application to Underdetermined Audio Source Separation

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      Pages 106-113

      Minimum Determinant Constraint for Non-negative Matrix Factorization

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      Pages 114-121

      Separation of Convolutive Mixtures with Hybrid Sources

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      Pages 122-129

      Blind Extraction of Chaotic Sources from White Gaussian Noise Based on a Measure of Determinism

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      Pages 130-137

      Estimating Squared-Loss Mutual Information for Independent Component Analysis

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      Pages 138-145

      Complete Blind Subspace Deconvolution

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      Pages 146-153

      Fast Parallel Estimation of High Dimensional Information Theoretical Quantities with Low Dimensional Random Projection Ensembles

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      Pages 154-162

      Theoretical Analysis and Comparison of Several Criteria on Linear Model Dimension Reduction

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