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The current disturbance classification of power quality data often has the problem of low disturbance recognition accuracy due to its large volume and difficult feature extraction.
Xin Xia +6 more
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A Compressed Sensing Approach for Distribution Matching [PDF]
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).
Mohamad Dia +2 more
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Dictionary Design for Distributed Compressive Sensing
This work is supported by EPSRC Research Grant EP/K033700/1 and EP/K033166/1, the Fundamental Research Funds for the Central Universities (No. 2014JBM149), the State Key Laboratory of Rail Traffic Control and Safety (RCS2012ZT014) of Beijing Jiaotong University, the Natural Science Foundation of China (U1334202), the Key Grant Project of Chinese ...
Wei Chen 0016 +2 more
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Distributed Compressive Sensing: A Deep Learning Approach [PDF]
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 +2 more
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The direction of arrival estimation method based on gridless compressed sensing
Efficient direction of arrival(DOA) estimation for densely distributed targets was a difficult and hot spot in current high-precision positioning technology.There were many problems and issuesfor existing DOA estimation methods which were designed based ...
GU Xu, WEI Shuang, LI Li, SU Ying
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Generalized Distributed Compressive Sensing
Distributed Compressive Sensing (DCS) improves the signal recovery performance of multi signal ensembles by exploiting both intra- and inter-signal correlation and sparsity structure. However, the existing DCS was proposed for a very limited ensemble of signals that has single common information \cite{Baron:2009vd}.
Park, Jeonghun +3 more
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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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Distributed Compressed Hyperspectral Sensing Imaging Incorporated Spectral Unmixing and Learning
Compressed hyperspectral imaging is a powerful technique for satellite-borne and airborne sensors that can effectively shift the complex computational burden from the resource-constrained encoding side to a presumably more capable base-station decoder ...
Hua Xiao +5 more
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Distributed Compressed Video Sensing in Camera Sensor Networks
With the booming of video devices ranging from low-power visual sensors to mobile phones, the video sequences captured by these simple devices must be compressed easily and reconstructed by relatively more powerful servers. In such scenarios, distributed
Yu Liu, Xuqi Zhu, Lin Zhang, Sung Ho Cho
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Distributed Compressed Sensing MRI Using Volume Array Coil
The volume array coil in the magnetic resonance imaging (MRI) system is a typical application of the distributed sensor network in the biomedical area.
Zhen Feng +6 more
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