Sequential sparse Bayesian learning with applications to system identification for damage assessment and recursive reconstruction of image sequences
type: Item
instance of: scholarly article
title: Sequential sparse Bayesian learning with applications to system identification for damage assessment and recursive reconstruction of image sequences
zbMATH Open document ID: 1506.62265
author: Yong Huang
author: James L. Beck
author: Hui Li
author: Yulong Ren
published in: Computer Methods in Applied Mechanics and Engineering
publication date: 2021-04-26T00:00:00Z
Mathematics Subject Classification ID: 62F15
Mathematics Subject Classification ID: 62L12
Mathematics Subject Classification ID: 65C20
Mathematics Subject Classification ID: 94A08
zbMATH DE Number: 7337811
zbMATH Keywords: sequential sparse Bayesian learning
zbMATH Keywords: hierarchical Bayesian model
zbMATH Keywords: recursive Bayesian estimation
zbMATH Keywords: uncertainty quantification
zbMATH Keywords: Bayesian system identification
zbMATH Keywords: Bayesian compressive sensing
describes a project that uses: PDCO
describes a project that uses: Yall1
describes a project that uses: ABC-SubSim
describes a project that uses: FPC_AS
MaRDI profile type: Publication
full work available at URL: j.cma.2020.113545
OpenAlex ID: W3103010819
cites work: Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
cites work: Compressed sensing
cites work: Atomic Decomposition by Basis Pursuit
cites work: A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation
cites work: Alternating Direction Algorithms for $\ell_1$-Problems in Compressive Sensing
cites work: Divide and conquer: an incremental sparsity promoting compressive sampling approach for polynomial chaos expansions
cites work: Sparse polynomial chaos expansions via compressed sensing and D-optimal design
cites work: 10.1162/15324430152748236
cites work: Sparse Bayesian Learning for Basis Selection
cites work: Bayesian system identification based on hierarchical sparse Bayesian learning and Gibbs sampling with application to structural damage assessment
cites work: Calibration of the stochastic multicloud model using Bayesian inference
cites work: Bayesian Compressive Sensing
cites work: Bayesian Compressive Sensing Via Belief Propagation
cites work: Exploiting Structure in Wavelet-Based Bayesian Compressive Sensing
cites work: Methods for Sparse Signal Recovery Using Kalman Filtering With Embedded Pseudo-Measurement Norms and Quasi-Norms
cites work: Time Invariant Error Bounds for Modified-CS-Based Sparse Signal Sequence Recovery
cites work: Recursive Recovery of Sparse Signal Sequences From Compressive Measurements: A Review
cites work: Approximate Bayesian computation by subset simulation
cites work: Using Approximate Bayesian Computation by Subset Simulation for Efficient Posterior Assessment of Dynamic State-Space Model Classes
cites work: An iterative Bayesian filtering framework for fast and automated calibration of DEM models
cites work: Probability Theory
cites work: Extensions of compressed sensing
DOI: 10.1016/J.CMA.2020.113545
description: scientific article; zbMATH DE number 7337811