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文章名:A New Generalized Alternating Direction Method of Multipliers for Separable Convex Programming and Its Applications to Image Deblurring with Wavelets 雜志:ICIC Express Letters 期卷:Volume 10, Issue 2, February 2016 作者:Hongchun Sun, Min Sun and Houchun Zhou |
版主 (文學(xué)泰斗)
風(fēng)雪
版主 (文學(xué)泰斗)
風(fēng)雪
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ccession number: 20160601888937 Title: A new generalized alternating direction method of multipliers for separable convex programming and its applications to image deblurring with wavelets Authors: Sun, Hongchun1 Email author sunhc68@163.com; Sun, Min2 Email author ziyouxiaodou@163.com; Zhou, Houchun1 Email author zhouhouchun@163.com Author affiliation: 1 School of Science Linyi University, Shuangling Street, Linyi, China 2 School of Mathematics and Statistics Zaozhuang University, Beian Road, Zaozhuang, China Source title: ICIC Express Letters Abbreviated source title: ICIC Express Lett. Volume: 10 Issue: 2 Issue date: February 1, 2016 Publication year: 2016 Pages: 271-277 Language: English ISSN: 1881803X Document type: Journal article (JA) Publisher: ICIC Express Letters Office Abstract: The classical alternating direction method of multipliers (ADMM), which is a special case of the famous proximal point algorithm, is well studied in the literature. In this paper, we propose a new generalized ADMM for separable convex programming, which is a modification of the classical ADMM by introducing an acceleration factor, and includes the latter as a special case. We prove the global convergence of the proposed method under some standard assumptions. Numerical experiments about image deblurring with wavelets are included to illustrate the efficiency of the new method. © 2016, ICIC Express Letters ICIC International. Number of references: 7 Main heading: Image enhancement Controlled terms: Algorithms - Convex optimization - Numerical methods - Variational techniques Uncontrolled terms: Acceleration factors - Alternating direction method of multipliers - Global conver-gence - Image deblurring - Numerical experiments - Proximal point algorithm - Standard assumptions - Variational inequalities Classification code: 921.2 Calculus - 921.6 Numerical Methods Database: Compendex Compilation and indexing terms, © |
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