Latent variable analysis and signal separation [electronic resource] : 12th International Conference, LVA/ICA 2015, Liberec, Czech Republic, August 25-28, 2015, Proceedings / Emmanuel Vincent, Arie Yeredor, Zbyněk Koldovský, Petr Tichavský (eds.).
2015
TK5102.9
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Title
Latent variable analysis and signal separation [electronic resource] : 12th International Conference, LVA/ICA 2015, Liberec, Czech Republic, August 25-28, 2015, Proceedings / Emmanuel Vincent, Arie Yeredor, Zbyněk Koldovský, Petr Tichavský (eds.).
Meeting Name
ISBN
9783319224824 electronic book
3319224824 electronic book
9783319224817
3319224824 electronic book
9783319224817
Published
Cham : Springer, 2015.
Language
English
Description
1 online resource (xvi, 532 pages) : illustrations.
Item Number
10.1007/978-3-319-22482-4 doi
Call Number
TK5102.9
Dewey Decimal Classification
621.382/2
Summary
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 ℓ́ℓ 29 accepted as oral presentations and 32 accepted as poster presentations ℓ́ℓ 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.
Note
International conference proceedings.
Includes author index.
Includes author index.
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Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed August 20, 2015).
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Series
Lecture notes in computer science ; 9237.
LNCS sublibrary. SL 1, Theoretical computer science and general issues.
LNCS sublibrary. SL 1, Theoretical computer science and general issues.
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Table of Contents
Tensor-based methods for blind signal separation
Deep neural networks for supervised speech separation/enhancment
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.
Deep neural networks for supervised speech separation/enhancment
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.