Latent variable analysis and signal ...
Clark Conference ((2005 :)

 

  • Latent variable analysis and signal separation[electronic resource] :12th International Conference, LVA/ICA 2015, Liberec, Czech Republic, August 25-28, 2015 : proceedings /
  • 紀錄類型: 書目-語言資料,印刷品 : Monograph/item
    杜威分類號: 621.3822
    書名/作者: Latent variable analysis and signal separation : 12th International Conference, LVA/ICA 2015, Liberec, Czech Republic, August 25-28, 2015 : proceedings // edited by Emmanuel Vincent ... [et al.].
    其他題名: LVA/ICA 2015
    其他作者: Vincent, Emmanuel.
    團體作者: Clark Conference
    出版者: Cham : : Springer International Publishing :, 2015.
    面頁冊數: xvi, 532 p. : : ill., digital ;; 24 cm.
    Contained By: Springer eBooks
    標題: Source separation (Signal processing) - Congresses.
    標題: Computer Science.
    標題: Pattern Recognition.
    標題: Image Processing and Computer Vision.
    標題: Simulation and Modeling.
    標題: Algorithm Analysis and Problem Complexity.
    標題: Discrete Mathematics in Computer Science.
    標題: Special Purpose and Application-Based Systems.
    ISBN: 9783319224824
    ISBN: 9783319224817
    內容註: Tensor-based methods for blind signal separation -- Deep neural networks for supervised speech separation/enhancment -- Joined analysis of multiple datasets, data fusion, and related topics -- Advances in nonlinear blind source separation -- Sparse and low rank modeling for acoustic signal processing.
    摘要、提要註: This book constitutes the proceedings of the 12th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICS 2015, held in Liberec, Czech Republic, in August 2015. The 61 revised full papers presented - 29 accepted as oral presentations and 32 accepted as poster presentations - were carefully reviewed and selected from numerous submissions. Five special topics are addressed: tensor-based methods for blind signal separation; deep neural networks for supervised speech separation/enhancement; joined analysis of multiple datasets, data fusion, and related topics; advances in nonlinear blind source separation; sparse and low rank modeling for acoustic signal processing.
    電子資源: http://dx.doi.org/10.1007/978-3-319-22482-4
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