Results 31 to 40 of about 2,877 (265)
Compressive Sensing Based on Mesoscopic Chaos of Silicon Optomechanical Photonic Crystal
IEEE Photonics Journal, 2020 Compressive sensing (CS) is an effective technique that can compress and recover sparse signals below the Nyquist-Shannon sampling theorem restriction.
Pengfei Guo +6 more
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Shock and Vibration, 2020 The compressive sensing (CS) theory provides a new slight to the big-data problem led by the Shannon sampling theorem in rolling element bearings condition monitoring, where the measurement matrix of CS tends to be designed by the random matrix (RM) to ...
Ya He, Kun Feng, Minghui Hu, Jinmiao Cui
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Application of Compressive Sensing in the Presence of Noise for Transient Photometric Events
Signals, 2022 Compressive sensing is a simultaneous data acquisition and compression technique, which can significantly reduce data bandwidth, data storage volume, and power. We apply this technique for transient photometric events. In this work, we analyze the effect
Asmita Korde-Patel +2 more
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Deformation Corrected Compressed Sensing (DC-CS): A Novel Framework for Accelerated Dynamic MRI
IEEE Transactions on Medical Imaging, 2015 We propose a novel deformation corrected compressed sensing (DC-CS) framework to recover dynamic magnetic resonance images from undersampled measurements. We introduce a generalized formulation that is capable of handling a wide class of sparsity/compactness priors on the deformation corrected dynamic signal.
Lingala, Sajan Goud +2 more
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AN IMPROVEMENT OF RESOURCE CONSUMPTION IN WIRELESS SENSOR NETWORK (WSN) USING COMPRESSIVE SENSING
Malaysian Journal of Computing, 2022 Wireless Sensor Network (WSN) refers to a group of spatially dispersed and dedicated sensors designed to monitor and record the physical conditions of the environment and organise the data collected at a central location.
Maizatul Akmal Ibrahim +1 more
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Automatic Modulation Recognition Using Compressive Cyclic Features
Algorithms, 2017 Higher-order cyclic cumulants (CCs) have been widely adopted for automatic modulation recognition (AMR) in cognitive radio. However, the CC-based AMR suffers greatly from the requirement of high-rate sampling.
Lijin Xie, Qun Wan
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Advanced Engineering Materials, EarlyView.This study explores the lightweight potential of laser additive‐manufactured NiTi triply periodic minimal surface sheet lattices. It systematically investigates the effects of relative density and unit cell size on surface quality, deformation recovery, compression behavior, and energy absorption.
Haoming Mo +3 more
wiley +1 more source
Unbalanced Expander Based Compressive Data Gathering in Clustered Wireless Sensor Networks
IEEE Access, 2017 Conventional compressive sensing-based data gathering (CS-DG) algorithms require a large number of sensors for each compressive sensing measurement, thereby resulting in high energy consumption in clustered wireless sensor networks (WSNs).
Xiangling Li, Xiaofeng Tao, Guoqiang Mao
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Elinvar Materials: Recent Progress and Challenges
Advanced Engineering Materials, EarlyView.Elinvar materials, exhibiting temperature‐invariant elastic modulus, are critical for precision instruments and emerging technologies. This article reviews recent progress in the field, with a focus on the anomalous thermoelastic behavior observed in key material systems.
Wenjie Li, Yang Ren
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Compressed sensing MRI with variable density averaging (CS-VDA) outperforms full sampling at low SNR [PDF]
Physics in Medicine & Biology, 2020 11 pages, 9 ...
Jasper Schoormans +4 more
openaire +4 more sources