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Latent Variable Analysis and Signal Separation [electronic resource] :10th International Conference, LVA/ICA 2012, Tel Aviv, Israel, March 12-15, 2012. Proceedings / edited by Fabian Theis, Andrzej Cichocki, Arie Yeredor, Michael Zibulevsky.

by Theis, Fabian [editor.]; Cichocki, Andrzej [editor.]; Yeredor, Arie [editor.]; Zibulevsky, Michael [editor.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Computer Science: 7191Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012.Description: XVI, 538p. online resource.ISBN: 9783642285516.Subject(s): Computer science | Software engineering | Computer software | Computational complexity | Computer simulation | Computer vision | Optical pattern recognition | Computer Science | Pattern Recognition | Image Processing and Computer Vision | Simulation and Modeling | Algorithm Analysis and Problem Complexity | Discrete Mathematics in Computer Science | Special Purpose and Application-Based SystemsDDC classification: 006.4 Online resources: Click here to access online In: Springer eBooksSummary: This book constitutes the proceedings of the 10th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2012, held in Tel Aviv, Israel, in Marchr 2012. The 20 revised full papers presented together with 42 revised poster papers, 1 keynote lecture, and 2 overview papers for the regular, as well as for the special session were carefully reviewed and selected from numerous submissions. Topics addressed are ranging from theoretical issues such as causality analysis and measures, through novel methods for employing the well-established concepts of sparsity and non-negativity for matrix and tensor factorization, down to a variety of related applications ranging from audio and biomedical signals to precipitation analysis.
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This book constitutes the proceedings of the 10th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2012, held in Tel Aviv, Israel, in Marchr 2012. The 20 revised full papers presented together with 42 revised poster papers, 1 keynote lecture, and 2 overview papers for the regular, as well as for the special session were carefully reviewed and selected from numerous submissions. Topics addressed are ranging from theoretical issues such as causality analysis and measures, through novel methods for employing the well-established concepts of sparsity and non-negativity for matrix and tensor factorization, down to a variety of related applications ranging from audio and biomedical signals to precipitation analysis.

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