论文标题
具有非均匀选择的随机支持和洞察力稀疏近似的一量
Submatrices with non-uniformly selected random supports and insights into sparse approximation
论文作者
论文摘要
在本文中,我们根据具有不均匀分布的支撑的随机子膜的规范得出了尾部界限。我们将这些结果应用于稀疏近似值,并对阈值,正交匹配追求和基础追求的平均病例性能进行分析。作为这些结果的应用,我们表征了传感词典以提高在不均匀情况下的平均性能,并以数值测试其性能。
In this paper we derive tail bounds on the norms of random submatrices with non-uniformly distributed supports. We apply these results to sparse approximation and conduct an analysis of the average case performance of thresholding, Orthogonal Matching Pursuit and Basis Pursuit. As an application of these results we characterise sensing dictionaries to improve average performance in the non-uniform case and test their performance numerically.