Sparse Recovery Using the Discrete Cosine Transform

被引：1

作者：

Barros, Benjamin ^{[1
]}

Johnson, Brody Dylan ^{[1
]}

机构：

[1] St Louis Univ, Dept Math & Stat, 220 North Grand Blvd, St Louis, MO 63103 USA

来源：

JOURNAL OF GEOMETRIC ANALYSIS | 2021年 / 31卷 / 09期

关键词：

Sparse recovery; Discrete cosine transform; Compressive sensing;

D O I：

10.1007/s12220-020-00574-0

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

This note considers the problem of sparse recovery in R-n from linear measurements associated with a discrete cosine transform. The main theorem shows that an s-sparse vector in R-n can be recovered from the first 2s coefficients of its discrete cosine transform. This theorem is a real-valued analog of a result in Foucart and Rauhut (A mathematical introduction to compressive sensing, applied and numerical harmonic analysis, Birkhauser/Springer, New York, 2013) concerned with sparse recovery in C-n based on linear measurements via the discrete Fourier transform.

引用

页码：8991 / 8998

页数：8

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