Eintrag weiter verarbeiten

Latent Variable Analysis and Signal Separation: 9th International Conference, LVA/ICA 2010, St. Malo, France, September 27-30, 2010. Proceedings

Gespeichert in:

Personen und Körperschaften: Vigneron, Vincent (VerfasserIn), Zarzoso, Vicente (Sonstige), Moreau, Eric (Sonstige), Gribonval, Rémi (Sonstige), Vincent, Emmanuel (Sonstige)
Titel: Latent Variable Analysis and Signal Separation: 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
Format: E-Book Konferenzbericht
Sprache: Englisch
veröffentlicht:
Berlin, Heidelberg Springer Berlin Heidelberg 2010
Gesamtaufnahme: SpringerLink
Lecture notes in computer science ; 6365
Schlagwörter:
Buchausg. u.d.T.: Latent variable analysis and signal separation, Berlin : Springer, 2010, XVIII, 655 S.
Quelle: Verbunddaten SWB
Zugangsinformationen: Elektronischer Volltext - Campuslizenz
Details
Zusammenfassung: 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.
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.
Umfang: Online-Ressource (XVIII, 655p. 182 illus, digital)
ISBN: 9783642159954
DOI: 10.1007/978-3-642-15995-4