Unscented compression sensing

Carmi, Avishy and Mihaylova, Lyudmila and Kanevsky, Dimitri (2012) Unscented compression sensing. In: Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on. IEEE, JPN, pp. 5249-5252. ISBN 978-1-4673-0045-2

Full text not available from this repository.

Abstract

In this paper we present a novel compressed sensing (CS) algorithm for the recovery of compressible, possibly time-varying, signal from a sequence of noisy observations. The newly derived scheme is based on the acclaimed unscented Kalman filter (UKF), and is essentially self reliant in the sense that no peripheral optimization or CS algorithm is required for identifying the underlying signal support. Relying exclusively on the UKF formulation, our method facilitates sequential processing of measurements by employing the familiar Kalman filter predictor corrector form. As distinct from other CS methods, and by virtue of its pseudo-measurement mechanism, the CS-UKF, as we termed it, is non iterative, thereby maintaining a computational overhead which is nearly equal to that of the conventional UKF.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
@inproceedings{DBLP:conf/icassp/CarmiMK12, author = {Avishy Carmi and Lyudmila Mihaylova and Dimitri Kanevsky}, title = {Unscented compressed sensing}, booktitle = {ICASSP}, year = {2012}, pages = {5249-5252}, ee = {http://dx.doi.org/10.1109/ICASSP.2012.6289104}, crossref = {DBLP:conf/icassp/2012}, bibsource = {DBLP, http://dblp.uni-trier.de} }
Uncontrolled Keywords:
/dk/atira/pure/researchoutput/libraryofcongress/qa75
Subjects:
ID Code:
56273
Deposited By:
Deposited On:
27 Jul 2012 13:11
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Jan 2020 05:33