Latent Variable Analysis and Signal Separation

13th International Conference, LVA/ICA 2017, Grenoble, France, February 21-23, 2017, Proceedings

Nonfiction, Computers, Advanced Computing, Engineering, Computer Vision, Application Software, Computer Graphics, General Computing
Cover of the book Latent Variable Analysis and Signal Separation by , Springer International Publishing
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Author: ISBN: 9783319535470
Publisher: Springer International Publishing Publication: February 13, 2017
Imprint: Springer Language: English
Author:
ISBN: 9783319535470
Publisher: Springer International Publishing
Publication: February 13, 2017
Imprint: Springer
Language: English

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. 

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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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