Cantitate/Preț
Produs
Total produse
Vezi coșul
Latent Variable Analysis and Signal Separation: 14th International Conference, LVA/ICA 2018, Guildford, UK, July 2–5, 2018, Proceedings de Yannick Deville

Latent Variable Analysis and Signal Separation: 14th International Conference, LVA/ICA 2018, Guildford, UK, July 2–5, 2018, Proceedings: Lecture Notes in Computer Science, cartea 10891

Editat de Yannick Deville, Sharon Gannot, Russell Mason, Mark D. Plumbley, Dominic Ward
en Limba Engleză Paperback – 6 iun 2018
This book constitutes the proceedings of the 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018, held in  Guildford, UK, in July 2018.
The 52 full papers  were carefully reviewed and selected from 62 initial submissions. 
As research topics the papers encompass a wide range of general mixtures of latent variables models but also theories and tools drawn from a great variety of disciplines such as structured tensor decompositions and applications; matrix and tensor factorizations; ICA methods; nonlinear mixtures; audio data and methods; signal separation evaluation campaign; deep learning and data-driven methods; advances in phase retrieval and applications; sparsity-related methods; and biomedical data and methods.
Citește tot Restrânge

Din seria Lecture Notes in Computer Science

Preț: 33418 lei

Preț vechi: 41772 lei
-20%

Puncte Express: 501
Preț estimativ în valută:
5908€ • 7044$ • 5124£

Carte tipărită la comandă

Livrare economică 16-30 martie

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă

Specificații

ISBN-13: 9783319937632
ISBN-10: 3319937634
Pagini: 552
Ilustrații: XVII, 580 p. 150 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.83 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Theoretical Computer Science and General Issues

Locul publicării:Cham, Switzerland

Cuprins

Structured Tensor Decompositions and Applications.- Matrix and Tensor Factorizations.- ICA Methods.- Nonlinear Mixtures.- Audio Data and Methods.- Signal Separation Evaluation Campaign.- Deep Learning and Data-driven Methods.- Advances in Phase Retrieval and Applications.- Sparsity-Related Methods.- Biomedical Data and Methods.