کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4605348 | 1337565 | 2009 | 22 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Sparse regression using mixed norms
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موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آنالیز ریاضی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Mixed norms are used to exploit in an easy way, both structure and sparsity in the framework of regression problems, and introduce implicitly couplings between regression coefficients. Regression is done through optimization problems, and corresponding algorithms are described and analyzed. Beside the classical sparse regression problem, multi-layered expansion on unions of dictionaries of signals are also considered. These sparse structured expansions are done subject to an exact reconstruction constraint, using a modified FOCUSS algorithm. When the mixed norms are used in the framework of regularized inverse problem, a thresholded Landweber iteration is used to minimize the corresponding variational problem.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied and Computational Harmonic Analysis - Volume 27, Issue 3, November 2009, Pages 303-324
Journal: Applied and Computational Harmonic Analysis - Volume 27, Issue 3, November 2009, Pages 303-324