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    Fusion of functional brain imaging modalities via linear programming.

    O Halchenko, Yaroslav and Pearlmutter, Barak A. and Hanson, Stephen Jose and Zaimi, Adi (2004) Fusion of functional brain imaging modalities via linear programming. Biomedical Engineering / Biomedizinische Technik, 48 (2). pp. 102-104. ISSN 0013-5585

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    Proposed method makes a number of simplifying assumptions which convert the EEG/FMRI integration problem into optimization of a convex function, of a form amenable to efficient solution as a very sparse linear programming (LP) problem. The assumptions made in doing this are, surprisingly, in general somewhat more robust than those generally used to cast EEG/FMRI integration as optimization of a non-convex function not amenable to efficient global optimization. This is because the L1 norm used here corresponds to a more robust statistical estimator than the L2 normal generally used For this reason, even though this technique results in a tractable global optimization, it is more robust to non-Gaussian noise and outliers than approaches that make the Gaussian noise assumption [1]. Current poster presents formulation of the problem together with results obtained on artificial data.

    Item Type: Article
    Keywords: Fusion; functional brain imaging; modalities; linear programming;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 12678
    Depositing User: Barak Pearlmutter
    Date Deposited: 01 Apr 2020 10:35
    Journal or Publication Title: Biomedical Engineering / Biomedizinische Technik
    Publisher: De Gruyter
    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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