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Fusion Forward-Backward Pursuit Algorithm for Compressed Sensing

机译:融合前向后追踪压缩算法

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The Forward-Backward Pursuit (FBP), which is a recently proposed method, receives wide attention due to the high reconstruction accuracy. In this paper, we use the fusion strategy and propose the Fusion Forward-Backward Pursuit (FFBP) algorithm. This strategy only needs the reconstruction information of two FBP with different parameters. According to the termination conditions of the FBP algorithm, FFBP adopts different operation strategies, during the signal reconstruction. Without other priori information, FFBP effectively improves the exact reconstruction rate, compared with the original algorithm. Moreover, FFBP, which fuses two FBP with non-optimal parameter, can reconstruct a better signal than a single FBP with optimal parameter. We demonstrate the advantage of the proposed method through numerical simulations.
机译:作为最近提出的方法,向前-向后追踪(FBP)由于高重构精度而受到广泛关注。在本文中,我们使用融合策略并提出融合前向后追踪(FFBP)算法。该策略仅需要两个具有不同参数的FBP的重建信息。根据FBP算法的终止条件,在信号重构过程中FFBP采用不同的运算策略。与原始算法相比,在没有其他先验信息的情况下,FFBP有效提高了准确的重建率。此外,将两个非最佳参数的FBP融合在一起的FFBP可以比具有最佳参数的单个FBP重建更好的信号。我们通过数值模拟证明了该方法的优势。

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