paper-with-me

Papers

Bayesian Hypothesis Testing for Block Sparse Signal Recovery

2015-08-22 · Mehdi Korki, Hadi Zayyani, Jingxin Zhang

This letter presents a novel Block Bayesian Hypothesis Testing Algorithm (Block-BHTA) for reconstructing block sparse signals with unknown block structures. The Block-BHTA comprises the detection and recovery of the supports, and the estimation of the amplitudes of the block sparse signal. The support detection and recovery is performed using a Bayesian hypothesis testing. Then, based on the detected and reconstructed supports, the nonzero amplitudes are estimated by linear MMSE. The effectiveness of Block-BHTA is demonstrated by numerical experiments.

📄 PDF Abstract BibTeX arXiv:1508.05495

Code (0)

등록된 구현이 없습니다.

Tasks

Two-sample testing

Similar Papers 제목 키워드 기반

Iterative Bayesian Reconstruction of Non-IID Block-Sparse Signals

2014-12-07 · Mehdi Korki, Jingxin Zhang, Cishen Zhang, Hadi Zayyani

This paper presents a novel Block Iterative Bayesian Algorithm (Block-IBA) for reconstructing block-sparse signals with unknown block structures. Unlike the existing algorithms for block sparse signal recovery which assu…

SPP-SBL: Space-Power Prior Sparse Bayesian Learning for Block Sparse Recovery

2025-05-13 · Yanhao Zhang, Zhihan Zhu, Yong Xia

The recovery of block-sparse signals with unknown structural patterns remains a fundamental challenge in structured sparse signal reconstruction. By proposing a variance transformation framework, this paper unifies exist…

parameter estimation

Bayesian hypothesis testing for one bit compressed sensing with sensing matrix perturbation

2015-11-18 · H. Zayyani, M. Korki, F. Marvasti

This letter proposes a low-computational Bayesian algorithm for noisy sparse recovery in the context of one bit compressed sensing with sensing matrix perturbation. The proposed algorithm which is called BHT-MLE comprise…

compressed sensingTwo-sample testing

General Total Variation Regularized Sparse Bayesian Learning for Robust Block-Sparse Signal Recovery

2021-02-13 · Aditya Sant, Markus Leinonen, Bhaskar D. Rao

Block-sparse signal recovery without knowledge of block sizes and boundaries, such as those encountered in multi-antenna mmWave channel models, is a hard problem for compressed sensing (CS) algorithms. We propose a novel…

compressed sensing

Pattern-Coupled Sparse Bayesian Learning for Recovery of Block-Sparse Signals

2013-11-09 · Jun Fang, Yanning Shen, Hongbin Li, Pu Wang

We consider the problem of recovering block-sparse signals whose structures are unknown \emph{a priori}. Block-sparse signals with nonzero coefficients occurring in clusters arise naturally in many practical scenarios. H…