Unscented compressed sensing
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 tha...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
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| Online Access: | https://hdl.handle.net/10356/85297 http://hdl.handle.net/10220/13412 |
| _version_ | 1811681305757220864 |
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| author | Carmi, Avishy Y. Mihaylova, Lyudmila. Kanevsky, Dimitri. |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Carmi, Avishy Y. Mihaylova, Lyudmila. Kanevsky, Dimitri. |
| author_sort | Carmi, Avishy Y. |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T03:38:50Z |
| format | Conference Paper |
| id | ntu-10356/85297 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:38:50Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/852972020-03-07T13:26:32Z Unscented compressed sensing Carmi, Avishy Y. Mihaylova, Lyudmila. Kanevsky, Dimitri. School of Mechanical and Aerospace Engineering International Conference on Acoustics, Speech and Signal Processing (2012 : Kyoto, Japan) 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. 2013-09-09T07:29:43Z 2019-12-06T16:01:03Z 2013-09-09T07:29:43Z 2019-12-06T16:01:03Z 2012 2012 Conference Paper https://hdl.handle.net/10356/85297 http://hdl.handle.net/10220/13412 10.1109/ICASSP.2012.6289104 en © 2012 IEEE |
| spellingShingle | Carmi, Avishy Y. Mihaylova, Lyudmila. Kanevsky, Dimitri. Unscented compressed sensing |
| title | Unscented compressed sensing |
| title_full | Unscented compressed sensing |
| title_fullStr | Unscented compressed sensing |
| title_full_unstemmed | Unscented compressed sensing |
| title_short | Unscented compressed sensing |
| title_sort | unscented compressed sensing |
| url | https://hdl.handle.net/10356/85297 http://hdl.handle.net/10220/13412 |
| work_keys_str_mv | AT carmiavishyy unscentedcompressedsensing AT mihaylovalyudmila unscentedcompressedsensing AT kanevskydimitri unscentedcompressedsensing |