Sparse Estimation using Bayesian Hierarchical Prior Modeling for Real and Complex Linear Models

In sparse Bayesian learning (SBL), Gaussian scale mixtures (GSMs) have been used to model sparsity-inducing priors that realize a class of concave penalty functions for the regression task in real-valued signal models. Motivated by the relative scarcity of formal tools for SBL in complex-valued mode...

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Veröffentlicht in:	arXiv.org 2014-10
Hauptverfasser:	Pedersen, Niels Lovmand, Carles Navarro Manchón, Mihai-Alin Badiu, Shutin, Dmitriy, Fleury, Bernard Henri
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bayesian analysis Machine learning Mathematical models Penalty function Regression analysis Robustness (mathematics) Statistics - Machine Learning
Online-Zugang:	Volltext
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