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Latent variable analysis and signal separation : 13th International Conference, LVA/ICA 2017, Grenoble, France, February 21-23, 2017, Proceedings / Petr Tichavský, Massoud Babaie-Zadeh, Olivier J.J. Michel, Nadège Thirion-Moreau (eds.).

By: Contributor(s): Material type: TextTextSeries: Lecture notes in computer science ; 10169. | LNCS sublibrary. SL 1, Theoretical computer science and general issues.Publisher: Cham, Switzerland : Springer, 2017Description: 1 online resource (xvi, 576 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319535470
  • 3319535471
Other title:
  • LVA/ICA 2017
Subject(s): Genre/Form: Additional physical formats: Print version:: Latent variable analysis and signal separation.DDC classification:
  • 621.382/2 23
LOC classification:
  • TK5102.9
Online resources: Summary: 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.
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International conference proceedings.

Includes author index.

Online resource; title from PDF title page (SpringerLink, viewed February 27, 2017).

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.

Includes bibliographical references and author index.

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