Title

Strong Impossibility Results for Sparse Signal Processing

Authors

Authors

V. Y. F. Tan;G. K. Atia

Comments

Authors: contact us about adding a copy of your work at STARS@ucf.edu

Abbreviated Journal Title

IEEE Signal Process. Lett.

Keywords

Blowing-up lemma; noisy group testing; sparse signal processing; strong; converse; support set; BOUNDS; Engineering, Electrical & Electronic

Abstract

This letter derives strong impossibility results for several sparse signal processing problems. It is shown that regardless of the allowed error probability in identifying the salient support set (as long as this probability is below one), the required number of measurements is almost the same as that required for the error probability to be arbitrarily small. Our proof technique involves the use of the blowing-up lemma and can be applied to diverse problems from noisy group testing to graphical model selection as long as the observations are discrete.

Journal Title

Ieee Signal Processing Letters

Volume

21

Issue/Number

3

Publication Date

1-1-2014

Document Type

Article

DOI Link

http://dx.doi.org/10.1109/lsp.2014.2298499

Language

English

First Page

260

Last Page

264

WOS Identifier

WOS:000330294300002

ISSN

1070-9908

Recommended Citation

"Strong Impossibility Results for Sparse Signal Processing" (2014). Faculty Bibliography 2010s. 6159.
https://stars.library.ucf.edu/facultybib2010/6159