Hypothesis Testing for Partial Sparse Recovery

被引：0

作者：

Tajer, Ali ^{[1
]}

Poor, H. Vincent ^{[1
]}

机构：

[1] Princeton Univ, Dept Elect Engn, Princeton, NJ 08544 USA

来源：

2012 50TH ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING (ALLERTON) | 2012年

关键词：

gamma; hypothesis testing; partial; sparsity; FALSE DISCOVERY RATE;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Traditionally, sparse recovery pursues the objective of reconstructing an information source that has a sparse representation in an appropriate basis. In such situations, full recovery of the support of the sparse signal is necessary as missing any point in the support penalizes the quality of the reconstructed signal. In certain applications, however, the ultimate objective is not to reconstruct an information source, and is rather to recover the sparse support only partially. This paper provides a hypothesis-testing framework for recovering any desired fraction of the supper and offers some asymptotic performance limits for the proposed tests.

引用

页码：901 / 908

页数：8

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