Discrete Uncertainty Principles and Sparse Signal Processing

被引：0

作者：

Afonso S. Bandeira

Megan E. Lewis

Dustin G. Mixon

机构：

[1] New York University,Department of Mathematics, Courant Institute of Mathematical Sciences

[2] Detachment 5,Department of Mathematics and Statistics

[3] Air Force Operational Test and Evaluation Center,undefined

[4] Air Force Institute of Technology,undefined

来源：

Journal of Fourier Analysis and Applications | 2018年 / 24卷

关键词：

Uncertainty principle; Sparsity; Compressed sensing;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

We develop new discrete uncertainty principles in terms of numerical sparsity, which is a continuous proxy for the 0-norm. Unlike traditional sparsity, the continuity of numerical sparsity naturally accommodates functions which are nearly sparse. After studying these principles and the functions that achieve exact or near equality in them, we identify certain consequences in a number of sparse signal processing applications.

引用

页码：935 / 956

页数：21

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