Data Gathering in Wireless Sensor Networks Based on Reshuffling Cluster Compressed Sensing by Lu Zhu, Baishan Ci, Yuanyuan Liu, Zhizhang (David) Chen

“…The existing compressed sensing (CS) based data gathering (CSDG) methods in wireless sensor networks (WSNs) usually assume that the sensed data are sparse or compressible. …”
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Improved Generalized Sparsity Adaptive Matching Pursuit Algorithm Based on Compressive Sensing by Zhao Liquan, Ma Ke, Jia Yanfei

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Compressed Sensing Based on the Characteristic Correlation of ECG in Hybrid Wireless Sensor Network by Weiwei Li, Ting Jiang, Ning Wang

“…One of the features of WBAN is that its power consumption and sampling rate should be restricted to a minimum. Compressed sensing (CS) is an emerging signal acquisition/compression methodology which offers a prominent alternative to traditional signal acquisition. …”
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On the Null Space Property of lq-Minimization for 0<q≤1 in Compressed Sensing by Yi Gao, Jigen Peng, Shigang Yue, Yuan Zhao

“…The paper discusses the relationship between the null space property (NSP) and the lq-minimization in compressed sensing. Several versions of the null space property, that is, the lq stable NSP, the lq robust NSP, and the lq,p robust NSP for 0<p≤q<1 based on the standard lq NSP, are proposed, and their equivalent forms are derived. …”
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Compressed sensing for electrocardiogram acquisition in wireless body sensor network: A comparative analysis by Junxin Chen, Jiazhu Xing, Leo Yu Zhang, Lin Qi

“…In the past decades, compressed sensing emerges as a promising technique for signal acquisition in low-cost sensor networks. …”
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Compressed Sensing/Sparse-Recovery Approach for Improved Range Resolution in Narrow-Band Radar by Sandra Costanzo

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High-Performance 3D Compressive Sensing MRI Reconstruction Using Many-Core Architectures by Daehyun Kim, Joshua Trzasko, Mikhail Smelyanskiy, Clifton Haider, Pradeep Dubey, Armando Manduca

“…Compressive sensing (CS) describes how sparse signals can be accurately reconstructed from many fewer samples than required by the Nyquist criterion. …”
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Augmented Lagrange Based on Modified Covariance Matching Criterion Method for DOA Estimation in Compressed Sensing by Weijian Si, Xinggen Qu, Lutao Liu

“…A novel direction of arrival (DOA) estimation method in compressed sensing (CS) is presented, in which DOA estimation is considered as the joint sparse recovery from multiple measurement vectors (MMV). …”
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A Bayesian Compressive Sensing Vehicular Location Method Based on Three-Dimensional Radio Frequency by Yunpeng Wang, Xuting Duan, Daxin Tian, Jianshan Zhou, Yingrong Lu, Guangquan Lu

“…With the goal of providing an efficient and reliable estimation of vehicular position in general traffic scenarios, we propose a hybrid TOA/DOA positioning method based on Bayesian compressive sensing (BCS), which benefits from the realization of vehicle-to-roadside wireless interaction with the dedicated short range communication. …”
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Compressed Sensing-Based Order Analysis for Blade Tip Timing Signals Measured at Varying Rotational Speed by Suiyu Chen, Yongmin Yang, Haifeng Hu, Fengjiao Guan, Guoji Shen, Faming Yang

“…To overcome these difficulties, a compressed sensing-based order analysis (CSOA) method was proposed. …”
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Fast Compressed Sensing MRI Based on Complex Double-Density Dual-Tree Discrete Wavelet Transform by Shanshan Chen, Bensheng Qiu, Feng Zhao, Chao Li, Hongwei Du

“…Compressed sensing (CS) has been applied to accelerate magnetic resonance imaging (MRI) for many years. …”
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Fast, super‐resolution sparse inverse synthetic aperture radar imaging via continuous compressive sensing by Lv Mingjiu, Ma Lei, Ma Jianchao, Chen Wenfeng, Yang Jun, Ma Xiaoyan, Cheng Qi

“…This paper proposes a fast, super‐resolution imaging method employing continuous compressive sensing for sparse‐aperture ISAR. First, the received echo in each range bin is characterised as a linear combination of multiple frequencies shown in a continuous atomic set, established into an atomic norm minimisation (ANM) mode. …”
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Low-Complexity Spatial-Temporal Filtering Method via Compressive Sensing for Interference Mitigation in a GNSS Receiver by Chung-Liang Chang, Guo-Shing Huang

“…A compressive sensing based array processing method is proposed to lower the complexity, and computation load of array system and to maintain the robust antijam performance in global navigation satellite system (GNSS) receiver. …”
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Compressive Sensing Based Bayesian Sparse Channel Estimation for OFDM Communication Systems: High Performance and Low Complexity by Guan Gui, Li Xu, Lin Shan, Fumiyuki Adachi

“…To improve the estimation performance, we proposed a compressive sensing based Bayesian sparse channel estimation (BSCE) method which cannot only exploit the channel sparsity but also mitigate the unexpected channel uncertainty without scarifying any computational complexity. …”
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Penggunaan Compressive Sensing pada Pengenalan Huruf dengan Tulisan Tangan Menggunakan Metode K-Nearest Neighbor by Zalfa Alif Muhammad, Gelar Budiman, Sofia Saidah

“…Dalam penelitian ini, dilakukan kompresi dengan teknik CS (Compressive Sensing). Penggunaan CS difokuskan terhadap pengenalan huruf kapital dan angka tulisan tangan yang didapatkan dari sebelas mahasiswa dengan beberapa skenario. …”
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Deep Learning Model for CS-Based Signal Recovery for IRS-Assisted Near-Field THz MIMO System by Vaishali Sharma, Prakhar Keshari, Sanjeev Sharma, Kuntal Deka, Ondrej Krejcar, Vimal Bhatia

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AI-Assisted Compressed Sensing Enables Faster Brain MRI for the Elderly: Image Quality and Diagnostic Equivalence with Conventional Imaging by Gu W, Yang C, Wang Y, Hu W, Wu D, Cai S, Hong G, Hu P, Zhang Q, Dai Y

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Application of Two-Dimensional Compressive Sensing to Wavelet Method of Moments for Fast Analysis of Wide-Angle Electromagnetic Scattering Problems by Yi Liu, Qi Qi, Xinyuan Cao, Mingsheng Chen, Guoqing Deng, Zhixiang Huang, Xianliang Wu

“…To efficiently solve the electromagnetic scattering problems over a wide incident angle, a novel scheme by introducing the two-dimensional compressive sensing theory into the wavelet method of moments is proposed. …”
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A Novel Compressed Sensing Method for Magnetic Resonance Imaging: Exponential Wavelet Iterative Shrinkage-Thresholding Algorithm with Random Shift by Yudong Zhang, Jiquan Yang, Jianfei Yang, Aijun Liu, Ping Sun

“…In the last decade, various rapid MRI techniques on the basis of compressed sensing (CS) were proposed. However, both computation time and reconstruction quality of traditional CS-MRI did not meet the requirement of clinical use. …”
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A Hybrid Approach for Fast Computation of Multiple Incident Angles Electromagnetic Scattering Problems with Compressive Sensing and Adaptive Cross Approximation by Guo-hua Wang, Yu-fa Sun

“…A hybrid compressive approach for fast computation of the electromagnetic scattering problems with multiple incident angles is proposed. The compressive sensing (CS) technique is firstly introduced to the method of moment (MoM) to reduce the number of the right-hand sides (RHS), but since the resulting excitation matrix contains linear dependency and has low-rank characteristics, the adaptive cross approximation (ACA) algorithm is used to recompress such excitation matrix, keeping only the necessary physical information. …”
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