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Weighted and Reweighted Approximate Message Passing

机译:加权和重新重量近似消息传递

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In this paper we derive weighted and reweighted AMP algorithms for signal reconstruction from compressed sensing measurements. Weighted AMP incorporates prior support information into the AMP algorithm and iteratively solves the weighted ?_1 minimization which is much faster than the usual linear programming algorithms used to solve this problem. We also introduce a reweighting scheme for regular and weighted AMP algorithms which enhances the recovery performance of both regular and weighted AMP while still maintaining the low complexity nature of AMP algorithms.
机译:在本文中,我们从压缩传感测量中获得了加权和重新重量的AMP算法,用于信号重建。加权放大器将先前的支持信息包含在AMP算法中,并迭代地解决了加权的?_1最小化,比通常的线性编程算法更快地解决了用于解决此问题的速度。我们还介绍了一种用于常规和加权AMP算法的重新传递方案,其增强了常规和加权放大器的恢复性能,同时仍然保持放大器算法的低复杂性。

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