Local adaptive joint sparse representation for hyperspectral image classification
Sign Up to like & getrecommendations! Published in 2019 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.01.034
Abstract: Abstract In this paper, a local adaptive joint sparse representation (LAJSR) model is proposed for the classification of hyperspectral remote sensing images. It improves the original joint sparse representation (JSR) method in both the signal… read more here.
Keywords: local adaptive; adaptive joint; sparse representation; representation ... See more keywords
Bayesian mmWave Channel Estimation via Exploiting Joint Sparse and Low-Rank Structures
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2910088
Abstract: We consider the problem of channel estimation for millimeter wave (mmWave) systems, where both the base station and the mobile station employ a single radio frequency (RF) chain to reduce the hardware cost and power… read more here.
Keywords: joint sparse; low rank; channel estimation; estimation ... See more keywords
An Armijo-Type Hard Thresholding Algorithm for Joint Sparse Recovery
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3097216
Abstract: Joint sparse recovery (JSR) in compressed sensing simultaneously recovers sparse signals with a common sparsity structure from their multiple measurement vectors obtained through a common sensing matrix. In this paper, we present an Armijo-type hard… read more here.
Keywords: armijo type; joint sparse; type hard; hard thresholding ... See more keywords
Bilateral Joint-Sparse Regression for Hyperspectral Unmixing
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2021.3115172
Abstract: Sparse hyperspectral unmixing has been a hot topic in recent years. Joint sparsity assumes that each pixel in a small neighborhood of hyperspectral images (HSIs) is composed of the same endmembers, which results in a… read more here.
Keywords: hyperspectral unmixing; bilateral joint; joint sparse; sparse regression ... See more keywords
Joint Sparse Autoencoder Based Massive MIMO CSI Feedback
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2023.3250716
Abstract: In frequency division duplex (FDD) based massive multiple-input multiple-output (MIMO) systems, the channel state information (CSI) feedback overhead could degrade spectrum and energy efficiency. Many works have made great progress in efficient feedback. However, previous… read more here.
Keywords: based massive; csi; feedback; joint sparse ... See more keywords
Joint Sparse Collaborative Regression on Imaging Genetics Study of Schizophrenia
Sign Up to like & getrecommendations! Published in 2022 at "IEEE/ACM Transactions on Computational Biology and Bioinformatics"
DOI: 10.1109/tcbb.2022.3172289
Abstract: The imaging genetics approach generates large amount of high dimensional and multi-modal data, providing complementary information for comprehensive study of Schizophrenia, a complex mental disease. However, at the same time, the variety of these data… read more here.
Keywords: collaborative regression; imaging genetics; sparse collaborative; joint sparse ... See more keywords
Self-Paced Joint Sparse Representation for the Classification of Hyperspectral Images
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2018.2865102
Abstract: In this paper, a self-paced joint sparse representation (SPJSR) model is proposed for the classification of hyperspectral images (HSIs). It replaces the least-squares (LS) loss in the standard joint sparse representation (JSR) model with a… read more here.
Keywords: representation; joint sparse; neighboring pixels; paced joint ... See more keywords
Reweighted Low-rank and Joint-sparse Unmixing With Library Pruning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3168932
Abstract: Sparse unmixing is a semi-supervised learning problem, which performs abundance estimation when a spectral library is given. In this way, the essence of sparse unmixing is to select the most suitable subset from the spectral… read more here.
Keywords: sparse; low rank; sparse unmixing; joint sparse ... See more keywords
Structured Joint Sparse Orthogonal Nonnegative Matrix Factorization for Fault Detection
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2023.3241990
Abstract: As modern industrial processes become complicated, and some faults are difficult to be detected due to noises and nonlinearity of data, data-driven fault detection (FD) has been extensively used to detect abnormal events in functional… read more here.
Keywords: structured joint; sparse orthogonal; fault detection; matrix factorization ... See more keywords
Efficient and Fast Joint Sparse Constrained Canonical Correlation Analysis for Fault Detection.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3201881
Abstract: The canonical correlation analysis (CCA) has attracted wide attention in fault detection (FD). To improve the detection performance, we propose a new joint sparse constrained CCA (JSCCCA) model that integrates the l2,0 -norm joint sparse… read more here.
Keywords: sparse; detection; correlation analysis; joint sparse ... See more keywords
Joint Sparse Graph for FBMC/OQAM Systems
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2018.2810638
Abstract: As an advanced nonorthogonal multiple access (NOMA) technique, the low density signature (LDS) has never been used in filter bank multicarrier (FBMC) systems. In this paper, we model a low density weight matrix (LDWM) to… read more here.
Keywords: low density; lds fbmc; sparse graph; joint sparse ... See more keywords