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Variational Bayesian Inference of Line Spectra
We target model order and parameter estimation via variational inference in a probabilistic model in which the frequencies are continuous-valued, i. e., not restricted to a grid; and the coefficients are governed by a Bernoulli-Gaussian prior model turning model order selection into binary sequence detection.
Sparse Estimation using Bayesian Hierarchical Prior Modeling for Real and Complex Linear Models
Motivated by the relative scarcity of formal tools for SBL in complex-valued models, this paper proposes a GSM model - the Bessel K model - that induces concave penalty functions for the estimation of complex sparse signals.
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