2020/12/03 by Simon Ruetz, Ruetz, Simon, Karin Schnass +1
Engineering · Mathematics · #FOS: Mathematics #Mathematical Approximation and Integration #Probability (math.PR) #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference
paper · pdf · doi:10.48550/arxiv.2012.02082
openalex publication_date 2020/12/03 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
In this paper we derive tail bounds on the norms of random submatrices with\nnon-uniformly distributed supports. We apply these results to sparse\napproximation and conduct an analysis of the average case performance of\nthresholding, Orthogonal Matching Pursuit and Basis Pursuit. As an application\nof these results we characterise sensing dictionaries to improve average\nperformance in the non-uniform case and test their performance numerically.\n