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Compressively Sensed Image Recognition [PDF]
2018 7th European Workshop on Visual Information Processing (EUVIP), 2018 6 pages, submitted/accepted, EUVIP ...
Degerli A. +4 more
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Hierarchical Compressed Sensing
, 2022 Compressed sensing is a paradigm within signal processing that provides the means for recovering structured signals from linear measurements in a highly efficient manner. Originally devised for the recovery of sparse signals, it has become clear that a similar methodology would also carry over to a wealth of other classes of structured signals. In this
Eisert, Jens +4 more
openaire +2 more sources
Quasi-linear Compressed Sensing [PDF]
Multiscale Modeling & Simulation, 2014 Inspired by significant real-life applications, in particular, sparse phase retrieval and sparse pulsation frequency detection in Asteroseismology, we investigate a general framework for compressed sensing, where the measurements are quasi-linear.
Martin Ehler +2 more
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Segmented Multistage Reconstruction of Magnetic Resonance Images
Advances in Electrical and Computer Engineering, 2021 Compressed sensing of magnetic resonance imaging refers to the reconstruction of magnetic resonance images from partially sampled k-space data. The k-space data reduces reconstruction processing time but at the cost of increasing artifacts - especially
FARIS, M. +3 more
doaj +1 more source
Measure What Should be Measured: Progress and Challenges in Compressive Sensing [PDF]
, 2012 Is compressive sensing overrated? Or can it live up to our expectations? What will come after compressive sensing and sparsity? And what has Galileo Galilei got to do with it? Compressive sensing has taken the signal processing community by storm. A large corpus of research devoted to the theory and numerics of compressive sensing has been published in
arxiv +1 more source
The Journal of Engineering, 2020 For the characteristics of a random distribution and a large number of buses in the power system, the authors introduce distributed compressed sensing to compress and reconstruct the power quality data. They built a distributed IEEE14 bus system in PSCAD.
Huanan Yu, Honghao Yu
doaj +1 more source
A novel cooperative spectrum signal detection algorithm for underwater communication system
EURASIP Journal on Wireless Communications and Networking, 2019 In order to further improve the spectrum resource detection probability and increase the spectrum utilization rate in underwater wireless communication systems, this paper designs a novel multi-layer cooperative spectrum sensing algorithm based on ...
Jiang Xiaolin +2 more
doaj +1 more source
Compressed Sensing in Hilbert Spaces [PDF]
, 2017 In many linear inverse problems, we want to estimate an unknown vector belonging to a high-dimensional (or infinite-dimensional) space from few linear measurements. To overcome the ill-posed nature of such problems, we use a low-dimension assumption on the unknown vector: it belongs to a low-dimensional model set. The question of whether it is possible
Traonmilin, Yann +3 more
openaire +6 more sources
Molecular Oncology, EarlyView.TOMM20 increases cancer aggressiveness by maintaining a reduced state with increased NADH and NADPH levels, oxidative phosphorylation (OXPHOS), and apoptosis resistance while reducing reactive oxygen species (ROS) levels. Conversely, CRISPR‐Cas9 knockdown of TOMM20 alters these cancer‐aggressive traits.
Ranakul Islam +9 more
wiley +1 more source
Evolution of compressed sensing theory and dynamic electric energy measurement method
Diance yu yibiaoThis paper expounds the evolution process of compressed sensing signal sparse model, measurement matrix construction, reconstruction algorithm design, compressed measurement and compressed sensing hardware signal processing system, and puts forward that ...
WU Wenqian, WANG Xuewei
doaj +1 more source