Arbitrary Block-Sparse Signal Reconstruction Based on Incomplete Single Measurement Vector
Sign Up to like & getrecommendations! Published in 2017 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-017-0528-3
Abstract: Within the compressive sensing framework, reconstruction algorithms of block-sparse signal (BSS) often have special requirements on sparsity patterns. As a result, only some particular BSSs can be reconstructed. In this paper, we present a new… read more here.
Keywords: reconstruction; block; sparse signal; sparsity ... See more keywords
Block Sparse Signal Recovery in Compressed Sensing: Optimum Active Block Selection and Within-Block Sparsity Order Estimation
Sign Up to like & getrecommendations! Published in 2018 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-017-0617-3
Abstract: In this paper, we develop a new algorithm for recovery of block sparse signals in compressed sensing framework based on orthogonal matching pursuit. Furthermore, we point out that a major issue in conventional sparse signal… read more here.
Keywords: recovery; order; block; sparse signal ... See more keywords
Compressively sensing nonadjacent block-sparse spectra via a block discrete chirp matrix
Sign Up to like & getrecommendations! Published in 2018 at "Photonic Network Communications"
DOI: 10.1007/s11107-018-0813-5
Abstract: The block-sparse structure is shared by many types of signals, including audio, image, and radar-emitted signals. This structure can considerably improve compressive sensing (CS) performance and has attracted much attention in recent years. However, when… read more here.
Keywords: block; block sparse; nonadjacent block; discrete chirp ... See more keywords
Block Sparse Bayesian Learning-Based Channel Estimation for MIMO-OTFS Systems
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2022.3144674
Abstract: In this letter, we propose an efficient channel estimation method for multiple input multiple output orthogonal time-frequency-space systems in which each delay path cluster of the channel has multiple Dopplers. Under the channel model, the… read more here.
Keywords: block sparse; channel estimation; based channel; estimation ... See more keywords
Covariance-Free Variational Bayesian Learning for Correlated Block Sparse Signals
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2023.3241316
Abstract: We consider the problem of estimating channel in massive machine type communication (mMTC) systems. The sparse device activity in a mMTC system makes the channel block-sparse, with intra-block correlation. Block-sparse Bayesian learning (B-SBL) is a… read more here.
Keywords: block sparse; variational bayesian; covariance free; block ... See more keywords
Block-Sparse Signal Recovery via General Total Variation Regularized Sparse Bayesian Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2022.3144948
Abstract: One of the main challenges in block-sparse signal recovery, as encountered in, e.g., multi-antenna mmWave channel models, is block-patterned estimation without knowledge of block sizes and boundaries. We propose a novel Sparse Bayesian Learning (SBL)… read more here.
Keywords: block sparse; sparse signal; block; sparse bayesian ... See more keywords
Joint Block Sparse Signal Recovery Problem and Applications in LTE Cell Search
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2016.2552247
Abstract: We consider the problem of jointly recovering block sparse signals that share the same support set, using multiple measurement vectors (MMVs). We consider the generalized MMV (GMMV) model wherein the different measurement vectors could have… read more here.
Keywords: recovery; problem; cell search; block sparse ... See more keywords
Spectral unmixing of hyperspectral images based on block sparse structure
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Applied Remote Sensing"
DOI: 10.1117/1.jrs.17.016510
Abstract: Abstract. Spectral unmixing (SU) of hyperspectral images (HSIs) is one of the important areas in remote sensing (RS) that needs to be carefully addressed in different RS applications. Despite the high spectral resolution of the… read more here.
Keywords: spectral unmixing; block sparse; hyperspectral images; unmixing hyperspectral ... See more keywords
A Regional Smoothing Block Sparse Bayesian Learning Method With Temporal Correlation for Channel Selection in P300 Speller
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Human Neuroscience"
DOI: 10.3389/fnhum.2022.875851
Abstract: The P300-based brain–computer interfaces (BCIs) enable participants to communicate by decoding the electroencephalography (EEG) signal. Different regions of the brain correspond to various mental activities. Therefore, removing weak task-relevant and noisy channels through channel selection… read more here.
Keywords: selection p300; block sparse; channel selection; sparse bayesian ... See more keywords