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Distributed Compressive Sensing Based Spectrum Sensing Method
2018For multi-antenna system, the difficulties of preforming spectrum sensing are high sampling rate and hardware cost. To alleviate these problems, we propose a novel utilization of distributed compressive sensing for the multi-antenna case. The multi-antenna signals first are sampled in terms of distributed compressive sensing, and then the time-domain ...
Yulong Gao, Yongkui Ma, Yanping Chen
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Simple and efficient algorithm for distributed compressed sensing
2008 IEEE Workshop on Machine Learning for Signal Processing, 2008In this paper we propose a new iterative thresholding algorithm for distributed compressed sensing (CS) based on a set of local cost functions referred as HALS-CS algorithm (compare with). This algorithm allows reconstructing all sources simultaneously by processing row by row of the compressed signals. Moreover, with an adaptive nonlinearly decreasing
Andrzej Cichocki +2 more
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Distributed Outlier Detection using Compressive Sensing
Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, 2015Computing outliers and related statistical aggregation functions from large-scale big data sources is a critical operation in many cloud computing scenarios, e.g. service quality assurance, fraud detection, or novelty discovery. Such problems commonly have to be solved in a distributed environment where each node only has a local slice of the entirety ...
Ying Yan +6 more
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A joint recovery algorithm for distributed compressed sensing
Transactions on Emerging Telecommunications Technologies, 2012ABSTRACTDistributed compressed sensing exploits the correlation among multiple signals to reduce the number of measurements required for recovery. In this paper, we propose a recovery algorithm for a type of joint sparsity model, where all signals share a common sparse component and each individual signal contains a sparse innovation component.
Wenbo Xu +3 more
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Perceptual-Based Distributed Compressed Video Sensing
2015 Data Compression Conference, 2015This paper proposes an approach of compressed sensing (CS) of video in which distributed video coding DVC and CS are integrated as in [1], and the sensing matrix is modulated in suit of [2] but with proposed fixed weighting strategy to certain DCT coefficients in an effort to improve the visual quality of reconstruction.
Sawsan Elsayed, Maha Elsabrouty
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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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Application of distributed compressed sensing for GMTI purposes
IET International Conference on Radar Systems (Radar 2012), 2012The first step of ground moving target indication is the differentiation between moving and nonmoving objects. Using sparsity based methods for this purpose is often constrained by the nonsparse characteristic of the nonmoving clutter. In this paper we present a new approach for moving target indication based on distributed compressed sensing, a ...
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Inequitable access to distributed energy resources due to grid infrastructure limits in California
Nature Energy, 2021Anna M Brockway, Duncan S Callaway
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Decentralized SDN Control Plane for a Distributed Cloud-Edge Infrastructure: A Survey
IEEE Communications Surveys and Tutorials, 2021Adrien Lebre
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