Reweighted linearized Bregman algorithm for sparse signal recovery

Chen Long, Tao Sun, Lizhi Cheng
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Abstract

In this paper, we present an efficient algorithm for sparse signal recovery with high exact recovery rate. The main idea of the algorithm is to combine two existing methods: linearized Bregman algorithm and reweighting technique. Compared with other available methods, such as reweighted Basis Pursuit (BP) and linearized Bregman, the proposed algorithm has a much lower computational complexity with higher probability of successful recovery. Numerical experiments demonstrate its efficiency and accuracy.
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稀疏信号恢复的重加权线性化Bregman算法
本文提出了一种精确恢复率高的稀疏信号恢复算法。该算法的主要思想是将现有的两种方法:线性化Bregman算法和重加权技术相结合。与现有的加权基追踪(BP)和线性化Bregman等方法相比,该算法具有较低的计算复杂度和较高的恢复成功率。数值实验证明了该方法的有效性和准确性。
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