Results 61 to 70 of about 3,276,837 (200)
Improved Bounds for Universal One-Bit Compressive Sensing
, 2017 Unlike compressive sensing where the measurement outputs are assumed to be real-valued and have infinite precision, in "one-bit compressive sensing", measurements are quantized to one bit, their signs.
Acharya, Jayadev +2 more
core +1 more source
Compressive-sensing data reconstruction for structural health monitoring: a machine-learning approach [PDF]
Structural Health Monitoring, 2019 Compressive sensing has been studied and applied in structural health monitoring for data acquisition and reconstruction, wireless data transmission, structural modal identification, and spare damage identification.
Y. Bao, Zhiyi Tang, Hui Li
semanticscholar +1 more source
Enhancing cooperation in MANET using neighborhood compressive sensing model
Egyptian Informatics Journal, 2021 This paper presents the use of Compressive Sensing (CS) in the reduction of resource consumption to minimize battery and bandwidth usage. It also focuses on how attacks and misbehavior can be nullified. The proposed Neighborhood Compressive Sensing (NCS)
Mohammad Amir Khusru Akhtar +1 more
doaj +1 more source
Robust Binary Fused Compressive Sensing using Adaptive Outlier Pursuit
, 2014 We propose a new method, {\it robust binary fused compressive sensing} (RoBFCS), to recover sparse piece-wise smooth signals from 1-bit compressive measurements. The proposed method is a modification of our previous {\it binary fused compressive sensing}
Figueiredo, Mário A. T. +1 more
core +1 more source
Lensless Imaging by Compressive Sensing
, 2013 In this paper, we propose a lensless compressive imaging architecture. The architecture consists of two components, an aperture assembly and a sensor. No lens is used. The aperture assembly consists of a two dimensional array of aperture elements.
Huang, Gang +3 more
core +1 more source
A Two-Dimensional Adaptive Target Detection Algorithm in the Compressive Domain
Sensors, 2019 By applying compressive sensing to infrared imaging systems, the sampling and transmitting time can be remarkably reduced. Therefore, in order to meet the real-time requirements of infrared small target detection tasks in the remote sensing field, many ...
Wenhuan Cao, Shucai Huang
doaj +1 more source
Heliyon, 2020 Combining the projection method of Solodov and Svaiter with the Liu-Storey and Fletcher Reeves conjugate gradient algorithm of Djordjević for unconstrained minimization problems, a hybrid conjugate gradient algorithm is proposed and extended to solve ...
A. Ibrahim +4 more
semanticscholar +1 more source
DR2-Net: Deep Residual Reconstruction Network for Image Compressive Sensing [PDF]
Neurocomputing, 2017 Most traditional algorithms for compressive sensing image reconstruction suffer from the intensive computation. Recently, deep learning-based reconstruction algorithms have been reported, which dramatically reduce the time complexity than iterative ...
Hantao Yao +5 more
semanticscholar +1 more source
Compressive Sensing for MIMO Radar
, 2009 Multiple-input multiple-output (MIMO) radar systems have been shown to achieve superior resolution as compared to traditional radar systems with the same number of transmit and receive antennas.
Petropulu, Athina P. +2 more
core +1 more source
Mitteilungen der Deutschen Mathematiker-Vereinigung, 2014 Jayaraman J. Tiagarajan +3 more
+8 more sources