Sparse Reconstruction of Sound Field Using Bayesian Compressive Sensing and Equivalent Source Method [PDF]
Sensors, 2023 To solve the problem of sound field reconstruction with fewer measurement points, a sound field reconstruction method based on Bayesian compressive sensing is proposed.
Yue Xiao +4 more
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Gradient Projection with Approximate L0 Norm Minimization for Sparse Reconstruction in Compressed Sensing [PDF]
Sensors, 2018 In the reconstruction of sparse signals in compressed sensing, the reconstruction algorithm is required to reconstruct the sparsest form of signal. In order to minimize the objective function, minimal norm algorithm and greedy pursuit algorithm are most ...
Ziran Wei +5 more
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Nonparametric Statistical Thresholding for Sparse Magnetoencephalography Source Reconstructions [PDF]
Frontiers in Neuroscience, 2012 Uncovering brain activity from MEG data requires solving an ill-posed inverse problem, greatly confounded by noise, interference, and correlated sources.
Julia Parsons Owen +4 more
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Sparse Reconstruction for Micro Defect Detection in Acoustic Micro Imaging [PDF]
Sensors, 2016 Acoustic micro imaging has been proven to be sufficiently sensitive for micro defect detection. In this study, we propose a sparse reconstruction method for acoustic micro imaging.
Yichun Zhang +6 more
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Near-Field 3D Sparse SAR Direct Imaging with Irregular Samples
Remote Sensing, 2022 Sparse imaging is widely used in synthetic aperture radar (SAR) imaging. Compared with the traditional matched filtering (MF) methods, sparse SAR imaging can directly image the scattered points of a target and effectively reduce the sidelobes and clutter
Shiqi Xing +5 more
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Sparse Reconstruction for Near-Field MIMO Radar Imaging Using Fast Multipole Method
IEEE Access, 2021 Radar imaging using multiple input multiple output systems are becoming popular recently. These applications typically contain a sparse scene and the imaging system is challenged by the requirement of high quality real-time image reconstruction from ...
Emre A. Miran +2 more
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Dynamic Orthogonal Matching Pursuit for Sparse Data Reconstruction
IEEE Open Journal of Signal Processing, 2023 The orthogonal matching pursuit (OMP) is one of the mainstream algorithms for sparse data reconstruction or approximation. It acts as a driving force for the development of several other greedy methods for sparse data reconstruction, and it also plays a ...
Yun-Bin Zhao, Zhi-Quan Luo
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Multi-Objective Sparse Reconstruction With Transfer Learning and Localized Regularization
IEEE Access, 2020 Multi-objective sparse reconstruction methods have shown strong potential in sparse reconstruction. However, most methods are computationally expensive due to the requirement of excessive functional evaluations.
Bai Yan +3 more
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Sparse signal reconstruction by swarm intelligence algorithms
Engineering Science and Technology, an International Journal, 2021 This study introduces a new technique for sparse signal reconstruction. In general, there are two classes of algorithms in the recovery of sparse signals: greedy approaches and l1-minimization methods. The proposed method employs swarm intelligence based
Murat Emre Erkoç, Nurhan Karaboğa
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Color Image Super-resolution Reconstruction Based on Color Constraint and Nonlocal Sparse Representation [PDF]
Jisuanji gongcheng, 2019 Color image super-resolution reconstruction method based on sparse representation model usually adopts sparse coding process based on image blocks,which easily leads to the instability of sparse representation,and the problems of detail blurring and ...
XU Zhigang, MA Qiang, ZHU Honglei, ZHANG Moyi
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