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Synthesis-based sparse reconstrucion with analysis-based solvers

机译：基于分析的求解器的基于合成的稀疏重构

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摘要

Synthesis sparsity model received great attention in the past decade. Signal reconstruction based analysis model appears recently and has a high accurate reconstruction rate., which constitutes a solid basis for practical applications. In this paper, we transform the sparse signal reconstruction issue of synthesis model to an analysis one with some additional restraints. Therefore the existing algorithms based on analysis model are able to solve the exact reconstruction problem of synthesis model. This approach is called the Synthesis-By-Analysis(SBA) approach. The proposed approach is evaluated by comparing it with the Orthogonal Matching Pursuit algorithm, which is a classic algorithm base on the synthesis model. Experiment results show that this approach is another option for reconstruction problem based on synthesis model, meanwhile allowing many algorithms for analysis cosparse model to be used for synthesis signal reconstruction as well.
机译：综合稀疏模型​​在过去的十年中受到了极大的关注。基于信号重构的分析模型最近出现，具有很高的准确重构率，为实际应用奠定了坚实的基础。在本文中，我们将综合模型的稀疏信号重构问题转化为一种具有一些附加约束的分析模型。因此，现有的基于分析模型的算法能够解决合成模型的精确重构问题。这种方法称为综合分析（SBA）方法。通过与正交匹配追踪算法进行比较，对所提出的方法进行了评估，该算法是基于综合模型的经典算法。实验结果表明，该方法是基于综合模型的重构问题的另一种选择，同时也允许许多分析稀疏模型的算法也可以用于综合信号的重构。

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