Sparse Bayesian Learning - an overview | ScienceDirect Topics
In [GLFW18], a sparse Bayesian learning (SBL) algorithm for the estimation of SMC and DMC parameters is introduced. The benefit of the SBL algorithm is that the number of SMC is …
A Sparse Bayesian Learning Algorithm for Estimation of …
5 days ago · To solve the inverse problem robustly, we develop a sparse Bayesian learning algorithm that incorporates informative priors for regularization, quantifies uncertainty, and …
Sparse Bayesian learning algorithm for separable dictionaries
Apr 1, 2021 · Dictionaries with separable structure reduce the computational load of sparse coding and learning algorithms and ensure that patterns present in 2D data are not broken by …
Abstract—Sparse Bayesian learning (SBL) is a powerful frame-work for tackling the sparse coding problem while also pro-viding uncertainty quantification. The most popular inference …
Improved Low-Complexity Sparse Bayesian Learning With Embedded Bayesian ...
Sparse Bayesian Learning (SBL) is recognized for its efficacy in sparse signal recovery, the computational demand escalates significantly with increasing data dimensionality due to the …
Sparse Bayesian learning with multiple dictionaries
Jun 1, 2019 · Sparse Bayesian learning (SBL) has emerged as a fast and competitive method to perform sparse processing. The SBL algorithm, which is developed using a Bayesian …
SPP-SBL: Space-Power Prior Sparse Bayesian Learning for Block Sparse …
4 days ago · The above problem has been extensively studied, and numerous algorithms have been developed to provide effective sparse solutions. Classic methods include Lasso [], Basis …
Sparse Bayesian learning using hierarchical synthesis prior for STAP
Feb 26, 2025 · This paper presents a sparse Bayesian learning algorithm using hierarchical synthesis priors for space–time adaptive processing. Compared with the traditional SR-STAP …
A Study and Comparison of Different Sparse Bayesian Learning Algorithms ...
This paper analyzes and compares the computation complexity of sparse Bayesian learning (SBL), multi-task sparse Bayesian learning (MSBL) and inverse-free sparse Bayesian learning …
A GAMP-Based Low Complexity Sparse Bayesian Learning Algorithm
Oct 19, 2017 · In this paper, we present an algorithm for the sparse signal recovery problem that incorporates damped Gaussian generalized approximate message passing (GGAMP) into …