3 accepted papers
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…
Sparse signal recovery algorithms like sparse Bayesian learning work well but the complexity quickly grows when tackling higher dimensional parametric dictionaries. In this work we propose a novel Bayesian strategy to address the two dimensional harmonic retrieval problem, through remodeling and rep…
In this paper we analyse the performance of Sparse Bayesian Learning (SBL) in an environment with correlated sources. We provide two new perspectives to understand SBL's strategy for handling correlated sources. Using a Minimum Power Distortionless Response (MPDR) beamformer-based perspective of SBL…