Results 271 to 280 of about 555,264 (327)

MRI at low field: A review of software solutions for improving SNR. [PDF]

NMR Biomed
Ayde R, Vornehm M, Zhao Y, Knoll F, Wu EX, Sarracanie M.   +5 more
europepmc   +1 more source

ERA5-SH: A global grided scale height dataset for tropospheric parameters based on ERA5 reanalysis. [PDF]

Sci Data
Hao R, Yang F, Li Z, Zhang Y, Zhou L, Wang L.   +5 more
europepmc   +1 more source

Biodegradable origami enables closed-loop sustainable robotic systems. [PDF]

Sci Adv
Wei P, Zhang Z, Cheng S, Meng Y, Tong M, Emu L, Yan W, Zhang Y, Wang Y, Zhao J, Xu C, Zhai F, Lu J, Wang L, Jiang H.   +14 more
europepmc   +1 more source

Compressed SENSitivity Encoding (SENSE): Qualitative and Quantitative Analysis. [PDF]

Diagnostics (Basel)
Picchi E, Minosse S, Pucci N, Di Pietro F, Serio ML, Ferrazzoli V, Da Ros V, Giocondo R, Garaci F, Di Giuliano F.   +9 more
europepmc   +1 more source

A Wide-Range, Highly Stable Intelligent Flexible Pressure Sensor Based on Micro-Wrinkled SWCNT/rGO-PDMS with Efficient Thermal Shrinkage. [PDF]

Biosensors (Basel)
Fan L, Wang Z, Yang T, Zhao Q, Wu Z, Wang Y, Qi X, Zhang L.   +7 more
europepmc   +1 more source

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Distributed Compressed Sensing

2015
This chapter first introduces CS in the conventional setting where one device acquires one signal and sends it to a receiver, and then extends it to the distributed framework in which multiple devices acquire multiple signals. In particular, we focus on two key problems related to the distributed setting. The former is the definition of sparsity models
Enrico Magli, Giulio Coluccia, Chiara Ravazzi   +2 more
openaire   +3 more sources

Distributed compressed sensing for despeckling of SAR images

Digital Signal Processing, 2018
Abstract Speckle noise is one of the critical disturbances that present in the radar imagery. This noise degrades the quality of synthetic aperture radar (SAR) images and needs to be reduced before using SAR images. This paper investigates a novel method for despeckling of SAR images in the distributed compressed sensing (DCS) framework.
Ahmad Shafiei, Mojtaba Beheshti, Ehsan Yazdian   +2 more
openaire   +3 more sources

Research on Distributed Compressed Sensing With Dynamic Block Sparsity for Underwater Acoustic Channel Estimation

IEEE Internet of Things Journal, 2023
Channel estimation plays a crucial role in Internet of Underwater Things networks. Traditional channel estimation algorithms have limited performance improvement under the block-sparsity underwater acoustic channel, and the distributed compressed sensing
Yuehai Zhou, Dongsheng Chen, F. Tong, A. Song   +3 more
semanticscholar   +1 more source