Latent Variable Analysis and Signal Separation

Beschreibung

This book constitutes the proceedings of the 12th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICS 2015, held in Liberec, Czech Republic, in August 2015. The 61 revised full papers presented – 29 accepted as oral presentations and 32 accepted as poster presentations – were carefully reviewed and selected from numerous submissions. Five special topics are addressed: tensor-based methods for blind signal separation; deep neural networks for supervised speech separation/enhancement; joined analysis of multiple datasets, data fusion, and related topics; advances in nonlinear blind source separation; sparse and low rank modeling for acoustic signal processing.
Up-to-date results Includes supplementary material: sn.pub/extras

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Emmanuel Vincent

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audio signal processing augmented statistics classification computational imaging decision trees deep learning empirical kernel maps environmental monitoring independent vector analysis joint block diagonalization medical imaging mobile sensor network multilinear algebra real-time similarity measures

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