Change Detection With Compressive Measurements

Keywords

Compressive measurements; concentration inequalities; quickest change detection

Abstract

Quickest change point detection is concerned with the detection of statistical change(s) in sequences while minimizing the detection delay subject to false alarm constraints. In this letter, the problem of change point detection is studied when the decision maker only has access to compressive measurements. First, an expression for the average detection delay of Shiryaev's procedure with compressive measurements is derived in the asymptotic regime where the probability of false alarm goes to zero. Second, the dependence of the delay on the compression ratio and the signal to noise ratio is explicitly quantified. The ratio of delays with and without compression is studied under various sensing matrix constructions, including Gaussian ensembles and random projections. For a target delay ratio, a sufficient condition on the number of measurements required to meet this objective with prespecified probability is derived.

Publication Date

2-1-2015

Publication Title

IEEE Signal Processing Letters

Volume

22

Issue

2

Number of Pages

182-186

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/LSP.2014.2352116

Socpus ID

84907219590 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84907219590

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