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Distributed compressed sensing for block-sparse signals
2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications, 2011To address the problems of high sampling rates, shadow fading and additive noise from the receiver, in this paper, a distributed compressed sampling (DCS) and centralized reconstruction approach which utilize the spatial diversity against fading channels is proposed.
Xing Wang +3 more
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Distributed Bayesian Compressive Sensing using Gibbs sampler
2012 International Conference on Wireless Communications and Signal Processing (WCSP), 2012Bayesian Compressive Sensing (BCS) observes s-parse signal from the statistics viewpoint. In BCS, a Bayesian hierarchy is established utilizing Bayesian inference, thus gives the reconstruction algorithm plenty of robust and flexibility. When dealing with distributed scenario, Bayesian hierarchy is also an effective method. Not only can statistic model
Hua Ai, Yang Lu, Wenbin Guo
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Compressive sensing in distributed applications
2010The theory of compressive sensing (CS) has recently been proposed as a framework for joint signal acquisition and compression by replacing the standard sample by sample measurement approach with the idea of collecting a set of random projections of the signal; it has already been successfully employed in a number of signal processing applications, e.g.,
GAETA, Rossano +2 more
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Rate-Distortion Theory of Distributed Compressed Sensing
2015In this chapter, correlated and distributed sources without cooperation at the encoder are considered. For these sources, the best achievable performance in the rate-distortion sense of any distributed compressed sensing scheme is derived, under the constraint of high-rate quantization.
Giulio Coluccia +2 more
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Decentralized SDN Control Plane for a Distributed Cloud-Edge Infrastructure: A Survey
IEEE Communications Surveys and Tutorials, 2021David Espinel, Adrien Lebre
exaly
Inequitable access to distributed energy resources due to grid infrastructure limits in California
Nature Energy, 2021Anna M Brockway, Duncan S Callaway
exaly
Distributed compressed sensing based on local transformer network
Information Sciences, 2023Yu Zhou +5 more
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Demystifying Parallel and Distributed Deep Learning
ACM Computing Surveys, 2020Tal Ben-Nun, Torsten Hoefler
exaly