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

共 50 条

[1] Bayesian Hypothesis Testing for Block Sparse Signal Recovery
Korki, Mehdi
Zayyani, Hadi
Zhang, Jingxin
IEEE COMMUNICATIONS LETTERS, 2016, 20 (03) : 494 - 497
[2] Sequential Testing for Sparse Recovery
Malloy, Matthew L.
Nowak, Robert D.
IEEE TRANSACTIONS ON INFORMATION THEORY, 2014, 60 (12) : 7862 - 7873
[3] Successive Hypothesis Testing Based Sparse Signal Recovery and Its Application to MUD in Random Access
Choi, Jinho
IEEE SIGNAL PROCESSING LETTERS, 2017, 24 (02) : 166 - 170
[4] Group Testing and Sparse Signal Recovery
Gilbert, Anna C.
Iwen, Mark A.
Strauss, Martin J.
2008 42ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, VOLS 1-4, 2008, : 1059 - +
[5] Hypothesis testing in sparse weighted stochastic block model
Mingao Yuan
Fan Yang
Zuofeng Shang
Statistical Papers, 2022, 63 : 1051 - 1073
[6] Hypothesis testing in sparse weighted stochastic block model
Yuan, Mingao
Yang, Fan
Shang, Zuofeng
STATISTICAL PAPERS, 2022, 63 (04) : 1051 - 1073
[7] Multiple Hypothesis Testing for Dynamic Support Recovery
Qiao, Heng
Pal, Piya
2017 IEEE 18TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC), 2017,
[8] HYPOTHESIS TESTING FOR HIGH-DIMENSIONAL SPARSE BINARY REGRESSION
Mukherjee, Rajarshi
Pillai, Natesh S.
Lin, Xihong
ANNALS OF STATISTICS, 2015, 43 (01): : 352 - 381
[9] Model selection via reweighted partial sparse recovery
Lu, Xiaofan
Ma, Huimei
Zhang, Linan
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2024, 438
[10] Partial Recovery Bounds for the Sparse Stochastic Block Model
Scarlett, Jonathan
Cevher, Volkan
2016 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, 2016, : 1904 - 1908

← 1 2 3 4 5 →