Signal reconstruction from noisy random projections

被引：377

作者：

Haupt, Jarvis ^{[1
]}

Nowak, Robert ^{[1
]}

机构：

[1] Univ Wisconsin, Dept Elect Engn, Madison, WI 53706 USA

来源：

IEEE TRANSACTIONS ON INFORMATION THEORY | 2006年 / 52卷 / 09期

基金：

美国国家科学基金会;

关键词：

complexity regularization; data compression; denoising; Rademacher chaos; random projections; sampling; wireless sensor networks;

D O I：

10.1109/TIT.2006.880031

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Recent results show that a relatively small number of random projections of a signal can contain most of its salient information. It follows that if a signal is compressible, in some orthonormal basis, then a very accurate reconstruction can be obtained from random projections. This "compressive sampling" approach is extended here to show that signals can be accurately recovered from random projections contaminated with noise. A practical iterative algorithm for signal reconstruction is proposed, and potential applications to coding, analog-digital (A/D) conversion, and remote wireless sensing are discussed.

引用

页码：4036 / 4048

页数：13

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