Title

Strong Impossibility Results For Sparse Signal Processing

Keywords

Blowing-up lemma; noisy group testing; sparse signal processing; strong converse; support set

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. © 1994-2012 IEEE.

Publication Date

3-1-2014

Publication Title

IEEE Signal Processing Letters

Volume

21

Issue

3

Number of Pages

260-264

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/LSP.2014.2298499

Socpus ID

84893350614 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84893350614

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