Results 31 to 40 of about 68,637 (294)
A Compressed Sensing Approach for Distribution Matching [PDF]
2018 IEEE International Symposium on Information Theory (ISIT), 2018 In this work, we formulate the fixed-length distribution matching as a Bayesian inference problem. Our proposed solution is inspired from the compressed sensing paradigm and the sparse superposition (SS) codes. First, we introduce sparsity in the binary source via position modulation (PM).
Laurent Schmalen +2 more
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On the Performance of Turbo Signal Recovery with Partial DFT Sensing Matrices [PDF]
, 2015 This letter is on the performance of the turbo signal recovery (TSR) algorithm for partial discrete Fourier transform (DFT) matrices based compressed sensing.
Ma, Junjie, Ping, Li, Yuan, Xiaojun
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Joint recovery algorithms using difference of innovations for distributed compressed sensing [PDF]
, 2013 Distributed compressed sensing is concerned with representing an ensemble of jointly sparse signals using as few linear measurements as possible. Two novel joint reconstruction algorithms for distributed compressed sensing are presented in this paper ...
Coluccia, Giulio +2 more
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Channel Impulse Response-based Distributed Physical Layer Authentication [PDF]
, 2017 In this preliminary work, we study the problem of {\it distributed} authentication in wireless networks. Specifically, we consider a system where multiple Bob (sensor) nodes listen to a channel and report their {\it correlated} measurements to a Fusion ...
Abbasi, Qammer H. +4 more
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Efficient distributed storage strategy based on compressed sensing for space information network
International Journal of Distributed Sensor Networks, 2016 This article investigates the distributed data storage problem with compressed sensing in the space information network. Since there exists a performance-energy trade-off, most existing strategies focus only on improving the compressed sensing ...
Bo Kong +4 more
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Distributed Compressive Sensing: A Deep Learning Approach [PDF]
IEEE Transactions on Signal Processing, 2016 Various studies that address the compressed sensing problem with Multiple Measurement Vectors (MMVs) have been recently carried. These studies assume the vectors of the different channels to be jointly sparse. In this paper, we relax this condition. Instead we assume that these sparse vectors depend on each other but that this dependency is unknown. We
Hamid Palangi, Rabab Ward, Li Deng
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Distributed Basis Pursuit [PDF]
, 2012 We propose a distributed algorithm for solving the optimization problem Basis Pursuit (BP). BP finds the least L1-norm solution of the underdetermined linear system Ax = b and is used, for example, in compressed sensing for reconstruction.
Aguiar, Pedro M. Q. +3 more
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Compressed sensing of monostatic and multistatic SAR [PDF]
, 2013 In this letter, we study the impact of compressed data collections from a synthetic aperture radar (SAR) sensor on the reconstruction quality of a scene of interest.
Cetin, Mujdat +3 more
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A distributed estimation method over network based on compressed sensing
International Journal of Distributed Sensor Networks, 2019 This article presents a distributed estimation method called compressed-combine-reconstruct-adaptive to estimate an unknown sparse parameter of interest from noisy measurement over networks based on compressed sensing.
Lin Li, Donghui Li
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International Journal of Distributed Sensor Networks, 2016 Energy-efficient data aggregation is important for underwater acoustic sensor networks due to its energy constrained character. In this paper, we propose a kind of energy-efficient data aggregation scheme to reduce communication cost and to prolong ...
Deqing Wang, Ru Xu, Xiaoyi Hu, Wei Su
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