论文标题
压缩感应的替代阈值规则
An Alternative Thresholding Rule for Compressed Sensing
论文作者
论文摘要
压缩传感算法通常使用硬阈值操作员从密集的向量传递到其最佳的S-Sparse近似值。但是，硬阈值操作员的输出不取决于特定问题实例中的任何信息。我们提出了一个替代的阈值规则，请向前看阈值。在本文中，我们为整个压缩传感的新阈值规则提供了理论和实验理由。
Compressed Sensing algorithms often make use of the hard thresholding operator to pass from dense vectors to their best s-sparse approximations. However, the output of the hard thresholding operator does not depend on any information from a particular problem instance. We propose an alternative thresholding rule, Look Ahead Thresholding, that does. In this paper we offer both theoretical and experimental justification for the use of this new thresholding rule throughout compressed sensing.
