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Title: Light-Weight Sequential SBL Algorithm: An Alternative to OMP
We present a Light-Weight Sequential Sparse Bayesian Learning (LWS-SBL) algorithm as an alternative to the orthogonal matching pursuit (OMP) algorithm for the general sparse signal recovery problem. The proposed approach formulates the recovery problem under the Type-II estimation framework and the stochastic maximum likelihood objective. We compare the computational complexity for the proposed algorithm with OMP and highlight the main differences. For the case of parametric dictionaries, a gridless version is developed by extending the proposed sequential SBL algorithm to locally optimize grid points near potential source locations and it is empirically shown that the performance approaches Cramer-Rao bound.´ Numerical results using the proposed approach demonstrate the support recovery performance improvements in different scenarios at a small computational price when compared to the OMP algorithm.  more » « less
Award ID(s):
2124929 2225617
PAR ID:
10417294
Author(s) / Creator(s):
;
Date Published:
Journal Name:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 2023
Page Range / eLocation ID:
1 to 5
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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