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    Sparse separation: principles and tricks

    Pearlmutter, Barak A. and Potluru, Vamsi K. (2003) Sparse separation: principles and tricks. Proceedings of SPIE, 5102. pp. 1-4. ISSN 0277-786X

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    Blind separation of linearly mixed white Gaussian sources is impossible, due to rotational symmetry. For this reason, all blind separation algorithms are based on some assumption concerning the fashion in which the situation departs from that insoluble case. Here we discuss the assumption of sparseness and try to put various algorithms that make the sparseness assumption in a common framework. The main objective of this paper is to give some rough intuitions, and to provide suitable hooks into the literature.

    Item Type: Article
    Additional Information: Citation: Barak A. Pearlmutter and Vamsi K. Potluru "Sparse separation: principles and tricks", Proc. SPIE 5102, Independent Component Analyses, Wavelets, and Neural Networks, 1 (April 4, 2003); doi:10.1117/12.502473;
    Keywords: Sparse separation; principles; tricks; algorithm;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 8138
    Identification Number:
    Depositing User: Barak Pearlmutter
    Date Deposited: 10 Apr 2017 12:25
    Journal or Publication Title: Proceedings of SPIE
    Publisher: SPIE
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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