4.5 Article

CONVERGENCE OF THE LINEARIZED BREGMAN ITERATION FOR l1-NORM MINIMIZATION

期刊

MATHEMATICS OF COMPUTATION
卷 78, 期 268, 页码 2127-2136

出版社

AMER MATHEMATICAL SOC
DOI: 10.1090/S0025-5718-09-02242-X

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  1. DSTA, Singapore
  2. ONR [N000140710810]
  3. Department of Defense
  4. National University of Singapore [R-146-000-113-112]

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One of the key steps in compressed sensing is to solve the basis pursuit problem min(u is an element of Rn){parallel to u parallel to(1) : Au = f}. Bregman iteration was very successfully used to solve this problem in [40]. Also, a simple and fast iterative algorithm based on linearized Bregman iteration was proposed in [40], which is described in detail with numerical simulations in [35]. A convergence analysis of the smoothed version of this algorithm was given in [11]. The purpose of this paper is to prove that the linearized Bregman iteration proposed in [40] for the basis pursuit problem indeed converges.

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