Abstract
The elastic net (EN) is a popular regularization and variable selection method that overcomes the shortcomings of Lasso such as poor recovery in the face of high mutual coherence. In this paper, we develop an efficient algorithm to solve the weighted EN criterion for complex-valued measurements applying the cyclic coordinate descent approach. We illustrate that usage of smartly chosen adaptive (i.e., data-dependent) weights revamps the algorithm to overcome the shortcomings of naive (non-weighted) EN and enhances the exact recovery. Usefulness of the proposed algorithm is illustrated for compressed beamforming (CBF) with the single-snapshot DoA (direction-of-arrival) estimation, in a demanding multi-source scenario that contains closely spaced sources having large variation in source powers. Accurate DoA's estimation performance and error plummet by the proposed algorithm validates its application and advocates its potential usage in other signal processing problems.
Original language | English |
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Title of host publication | 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016 |
Publisher | IEEE |
Pages | 197-201 |
Number of pages | 5 |
ISBN (Electronic) | 9781509029204 |
DOIs | |
Publication status | Published - 15 Nov 2016 |
MoE publication type | A4 Article in a conference publication |
Event | International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing - Aachen, Germany Duration: 19 Sep 2016 → 22 Sep 2016 Conference number: 4 http://workshops.fhr.fraunhofer.de/cosera/ |
Workshop
Workshop | International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing |
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Abbreviated title | CoSeRa |
Country | Germany |
City | Aachen |
Period | 19/09/2016 → 22/09/2016 |
Internet address |