3 papers
eess.SP2026
Total Variation Sparse Bayesian Learning for Block Sparsity via Majorization-Minimization
Yanbin He, Geethu Joseph
Block sparsity is a widely exploited structure in sparse recovery, offering significant gains when signal blocks are known. Yet, practical signals often exhibit unknown block bound…
eess.SP2024
Efficient Off-Grid Bayesian Parameter Estimation for Kronecker-Structured Signals
Yanbin He, Geethu Joseph
This work studies the problem of jointly estimating unknown parameters from Kronecker-structured multidimensional signals, which arises in applications like intelligent reflecting…
eess.SP2023
Bayesian Algorithms for Kronecker-structured Sparse Vector Recovery With Application to IRS-MIMO Channel Estimation
Yanbin He, Geethu Joseph
We study the sparse recovery problem with an underdetermined linear system characterized by a Kronecker-structured dictionary and a Kronecker-supported sparse vector. We cast this…