Paper Info
Title
When "exact recovery" is exact recovery in compressed sensing simulation.
Abstract
In a simulation of compressed sensing (CS), one must test whether the recovered solution (x) over cap is the true solution x, i.e., "exact recovery." Most CS simulations employ one of two criteria: 1) the recovered support is the true support; or 2) the normalized squared error is less than epsilon(2). We analyze these exact recovery criteria independent of any recovery algorithm, but with respect to signal distributions that are often used in CS simulations. That is, given a pair ((x) over cap, x), when does "exact recovery" occur with respect to only one or both of these criteria for a given distribution of x? We show that, in a best case scenario, epsilon(2) sets a maximum allowed missed detection rate in a majority sense.
Year
Venue
Keywords
2012
European Signal Processing Conference
compressed sensing,exact recovery
Field
DocType
ISSN
Mathematical optimization,Normalization (statistics),Algorithm,Mean squared error,Signal reconstruction,Mathematics,Compressed sensing
Conference
2076-1465
Citations 
PageRank 
References 
0
0.34
10
Authors
1
Name
Order
Citations
PageRank
Bob L. Sturm124129.88