1.

Record Nr.

UNINA9910483817003321

Titolo

Latent Variable Analysis and Signal Separation [[electronic resource] ] : 9th International Conference, LVA/ICA 2010, St. Malo, France, September 27-30, 2010, Proceedings / / edited by Vincent Vigneron, Vicente Zarzoso, Eric Moreau, Rémi Gribonval, Emmanuel Vincent

Pubbl/distr/stampa

Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010

ISBN

1-280-38934-6

9786613567260

3-642-15995-8

Edizione

[1st ed. 2010.]

Descrizione fisica

1 online resource (XVIII, 655 p. 182 illus.)

Collana

Theoretical Computer Science and General Issues, , 2512-2029 ; ; 6365

Disciplina

519.5/35

Soggetti

Pattern recognition systems

Computer vision

Computer simulation

Algorithms

Computer science—Mathematics

Discrete mathematics

Computers, Special purpose

Automated Pattern Recognition

Computer Vision

Computer Modelling

Discrete Mathematics in Computer Science

Special Purpose and Application-Based Systems

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibliographic Level Mode of Issuance: Monograph

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Speech and Audio Applications -- Convolutive Signal Separation -- The 2010 Signal Separation Evaluation Campaign (SiSEC2010) -- Audio -- Theory -- Telecom -- Tensor Factorizations -- Sparsity I -- Sparsity; Biomedical Applications -- Non-negativity; Image Processing Applications -- Tensors; Joint Diagonalization -- Sparsity II -- Biomedical Applications -- Emerging Topics.



Sommario/riassunto

This book constitutes the proceedings of the 9th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2010, held in St. Malo, France, in September 2010. The 25 papers presented were carefully reviewed and selected from over hundred submissions. The papers collected in this volume demonstrate that the research activity in the field continues to gather theoreticians and practitioners, with contributions ranging range from abstract concepts to the most concrete and applicable questions and considerations. Speech and audio, as well as biomedical applications, continue to carry the mass of the considered applications. Unsurprisingly the concepts of sparsity and non-negativity, as well as tensor decompositions, have become predominant, reflecting the strong activity on these themes in signal and image processing at large.