DocumentCode :
3462147
Title :
One-step-ahead kinematic compressive sensing
Author :
Hover, F.S. ; Hummel, R. ; Mitra, U. ; Sukhatme, G.
Author_Institution :
Dept. Mech. Eng., Massachusetts Inst. of Technol., Cambridge, MA, USA
fYear :
2011
fDate :
5-9 Dec. 2011
Firstpage :
1314
Lastpage :
1319
Abstract :
A large portion of work on compressive sampling and sensing has focused on reconstructions from a given measurement set. When the individual samples are expensive and optional, as is the case with autonomous agents operating in a physical domain and under specific energy limits, the CS problem takes on a new aspect because the projection is column-sparse, and the number of samples is not necessarily large. As a result, random sampling may no longer be the best tactic. The underlying incoherence properties in l0 reconstruction, however, can still motivate the purposeful design of samples in planning for CS with one or more agents; we develop here a greedy and computationally tractable sampling rule that will improve errors relative to random points. Several example cases illustrate that the approach is effective and robust.
Keywords :
compressed sensing; greedy algorithms; signal reconstruction; signal sampling; autonomous agents; column-sparse projection; compressive sampling; computational tractable sampling rule; greedy sampling rule; measurement set; one-step-ahead kinematic compressive sensing; random sampling; signal reconstruction; Coherence; Compressed sensing; Dictionaries; Image reconstruction; Noise; Planning; Transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
GLOBECOM Workshops (GC Wkshps), 2011 IEEE
Conference_Location :
Houston, TX
Print_ISBN :
978-1-4673-0039-1
Electronic_ISBN :
978-1-4673-0038-4
Type :
conf
DOI :
10.1109/GLOCOMW.2011.6162400
Filename :
6162400
Link To Document :
بازگشت