Latent Variable Analysis and Signal Separation

1. Front Matter

   Pages I-XVI

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2. Tensor Approaches

   1. Front Matter

      Pages 1-1

      PDF

   2. Higher-Order Block Term Decomposition for Spatially Folded fMRI Data

      • Christos Chatzichristos, Eleftherios Kofidis, Yiannis Kopsinis, Manuel Morante Moreno, Sergios Theodoridis

      Pages 3-15

   3. Modeling Parallel Wiener-Hammerstein Systems Using Tensor Decomposition of Volterra Kernels

      • Philippe Dreesen, David T. Westwick, Johan Schoukens, Mariya Ishteva

      Pages 16-25

   4. Fast Nonnegative Matrix Factorization and Completion Using Nesterov Iterations

      • Clément Dorffer, Matthieu Puigt, Gilles Delmaire, Gilles Roussel

      Pages 26-35

   5. Blind Source Separation of Single Channel Mixture Using Tensorization and Tensor Diagonalization

      • Anh-Huy Phan, Petr Tichavský, Andrzej Cichocki

      Pages 36-46

   6. High-Resolution Subspace-Based Methods: Eigenvalue- or Eigenvector-Based Estimation?

      • Konstantin Usevich, Souleymen Sahnoun, Pierre Comon

      Pages 47-56

3. From Source Positions to Room Properties: Learning Methods for Audio Scene Geometry Estimation

   1. Front Matter

      Pages 57-57

      PDF

   2. Speaker Tracking on Multiple-Manifolds with Distributed Microphones

      • Bracha Laufer-Goldshtein, Ronen Talmon, Sharon Gannot

      Pages 59-67

   3. VAST: The Virtual Acoustic Space Traveler Dataset

      • Clément Gaultier, Saurabh Kataria, Antoine Deleforge

      Pages 68-79

   4. Sketching for Nearfield Acoustic Imaging of Heavy-Tailed Sources

      • Mathieu Fontaine, Charles Vanwynsberghe, Antoine Liutkus, Roland Badeau

      Pages 80-88

   5. Acoustic DoA Estimation by One Unsophisticated Sensor

      • Dalia El Badawy, Ivan Dokmanić, Martin Vetterli

      Pages 89-98

   6. Acoustic Source Localization by Combination of Supervised Direction-of-Arrival Estimation with Disjoint Component Analysis

      • Jörn Anemüller, Hendrik Kayser

      Pages 99-108

4. Tensors and Audio

   1. Front Matter

      Pages 109-109

      PDF

   2. An Initialization Method for Nonlinear Model Reduction Using the CP Decomposition

      • Gabriel Hollander, Philippe Dreesen, Mariya Ishteva, Johan Schoukens

      Pages 111-120

   3. Audio Zoom for Smartphones Based on Multiple Adaptive Beamformers

      • Ngoc Q. K. Duong, Pierre Berthet, Sidkièta Zabre, Michel Kerdranvat, Alexey Ozerov, Louis Chevallier

      Pages 121-130

   4. Complex Valued Robust Multidimensional SOBI

      • Niko Lietzén, Klaus Nordhausen, Pauliina Ilmonen

      Pages 131-140

   5. Ego Noise Reduction for Hose-Shaped Rescue Robot Combining Independent Low-Rank Matrix Analysis and Multichannel Noise Cancellation

      • Narumi Mae, Masaru Ishimura, Shoji Makino, Daichi Kitamura, Nobutaka Ono, Takeshi Yamada et al.

      Pages 141-151

   6. Some Theory on Non-negative Tucker Decomposition

      • Jeremy E. Cohen, Pierre Comon, Nicolas Gillis

      Pages 152-161

   7. A New Algorithm for Multimodal Soft Coupling

      • Farnaz Sedighin, Massoud Babaie-Zadeh, Bertrand Rivet, Christian Jutten

      Pages 162-171

This book constitutes the proceedings of the 13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017, held in Grenoble, France, in Feburary 2017. The 53 papers presented in this volume were carefully reviewed and selected from 60 submissions. They were organized in topical sections named: tensor approaches; from source positions to room properties: learning methods for audio scene geometry estimation; tensors and audio; audio signal processing; theoretical developments; physics and bio signal processing; latent variable analysis in observation sciences; ICA theory and applications; and sparsity-aware signal processing. 

• blind signal separation
• dereverbation and denoising
• independent component analysis
• speech and audio separation
• tensor decomposition
• brain-computer interface
• constrained optimization
• crowdsourcing
• deep neural networks
• hyperspectral imaging
• latent variable analysis
• linear programming
• machine learning
• model-independent
• multimodality
• neuroscience
• non-negative matrix factorization
• room simulation
• sparsity-promoting methods

• Institute of Information Theory and Automation, Prague, Czech Republic

  Petr Tichavský

• Sharif University of Technology, Tehran, Iran

  Massoud Babaie-Zadeh

• Grenoble-Alpes University, Grenoble, France

  Olivier J.J. Michel

• Toulon University, Toulon, France

  Nadège Thirion-Moreau

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