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Message-passing algorithms for compressed sensing [PDF]
Proceedings of the National Academy of Sciences of the United States of America, 2009 Compressed sensing aims to undersample certain high-dimensional signals yet accurately reconstruct them by exploiting signal characteristics. Accurate reconstruction is possible when the object to be recovered is sufficiently sparse in a known basis ...
David L. Donoho +2 more
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Compressed sensing in fluorescence microscopy.
Progress in Biophysics and Molecular Biology, 2021 Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from under-sampled data with respect to the Nyquist criterium. CS exploits sparsity constraints based on the knowledge of prior information, relative to the structure of the object in the spatial or other domains.
Gianmaria Calisesi +6 more
semanticscholar +7 more sources
Overview of Compressed Sensing: Sensing Model, Reconstruction Algorithm, and Its Applications
Applied Sciences, 2020 With the development of intelligent networks such as the Internet of Things, network scales are becoming increasingly larger, and network environments increasingly complex, which brings a great challenge to network communication.
Lixiang Li +5 more
doaj +2 more sources
Compressed Sensing for Biomedical Photoacoustic Imaging: A Review [PDF]
SensorsPhotoacoustic imaging (PAI) is a rapidly developing emerging non-invasive biomedical imaging technique that combines the strong contrast from optical absorption imaging and the high resolution from acoustic imaging.
Yuanmao Wang +3 more
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Compressed Sensing Based Channel Estimation for Movable Antenna Communications [PDF]
IEEE Communications Letters, 2023 In this letter, we study the channel estimation for wireless communications with movable antenna (MA), which requires to reconstruct the channel response at any location in a given region where the transmitter/receiver is located based on the channel ...
Wenyan Ma, Lipeng Zhu, Rui Zhang
semanticscholar +1 more source
Integrated Sensing and Communication With mmWave Massive MIMO: A Compressed Sampling Perspective [PDF]
IEEE Transactions on Wireless Communications, 2022 Integrated sensing and communication (ISAC) has opened up numerous game-changing opportunities for realizing future wireless systems. In this paper, we propose an ISAC processing framework relying on millimeter-wave (mmWave) massive multiple-input ...
Zhen Gao +6 more
semanticscholar +1 more source
Single-Shot Compressed Imaging via Random Phase Modulation
Applied Sciences, 2022 Compressed sensing (CS) provides an innovative framework for signal sampling, which enables accurate recovery of the sparse or compressible signal from a small set of linear measurements far fewer than the Nyquist rate in traditional signal processing ...
Cheng Zhang +5 more
doaj +1 more source
Distributed Compressed Sensing of Hyperspectral Images According to Spectral Library Matching
IEEE Access, 2021 The ever-increasing resolution puts tremendous pressure to the onboard hyperspectral imaging system. Compressed sensing technology is one of the important ways to solve this problem.
Hua Xiao, Zhongliang Wang, Xueying Cui
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Compressed Sensing: Theory and Applications
Journal of Physics: Conference Series, 2023 Compressed sensing is a new technique for solving underdetermined linear systems. Because of its good performance, it has been widely used in academia.
Hanbo Wang
semanticscholar +1 more source
Applied and Computational Harmonic Analysis, 2023 We introduce the broad subclass of algebraic compressed sensing problems, where structured signals are modeled either explicitly or implicitly via polynomials. This includes, for instance, low-rank matrix and tensor recovery. We employ powerful techniques from algebraic geometry to study well-posedness of sufficiently general compressed sensing ...
Breiding, Paul +3 more
openaire +2 more sources