Results 1 to 10 of about 799,916 (290)
Local-set-based Graph Signal Reconstruction
IEEE Transactions on Signal Processing, 2015 Signal processing on graph is attracting more and more attentions. For a graph signal in the low-frequency subspace, the missing data associated with unsampled vertices can be reconstructed through the sampled data by exploiting the smoothness of the ...
Gu, Yuantao, Liu, Pengfei, Wang, Xiaohan
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A Faster and More Accurate Iterative Threshold Algorithm for Signal Reconstruction in Compressed Sensing [PDF]
Sensors, 2022 Fast iterative soft threshold algorithm (FISTA) is one of the algorithms for the reconstruction part of compressed sensing (CS). However, FISTA cannot meet the increasing demands for accuracy and efficiency in the signal reconstruction. Thus, an improved
Jianxiang Wei +5 more
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Improvement of NSL0 algorithm based on compressed sensing theory
Dianzi Jishu Yingyong, 2021 Compressed sensing theory provides a new way of signal acquisition.The signal is sparse transformed, and a few observed values are used to reconstruct the signal with high precision.Among them, the signal reconstruction method is the core of compressed ...
Tao Liang, Liu Haipeng, Wang Meng
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Pulsed Terahertz Signal Reconstruction [PDF]
Journal of Applied Physics, 2007 A procedure is outlined which can be used to determine the response of an experimental sample to a single, simple broadband frequency pulse in terahertz frequency time domain spectroscopy (TDS). The advantage that accrues from this approach is that oscillations and spurious signals (arising from a variety of sources in the TDS system or from ambient ...
Fletcher, J.R. +4 more
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Remote Sensing, 2021 Azimuth non-uniform signal-reconstruction is a critical step for azimuth multi-channel high-resolution wide-swath (HRWS) synthetic aperture radar (SAR) data processing.
Ning Li +4 more
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IET Signal Processing, 2023 Due to its self‐regularising nature and its ability to quantify uncertainty, the Bayesian approach has achieved excellent recovery performance across a wide range of sparse signal recovery applications.
Zonglong Bai +3 more
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Improved Compressed Sensing Reconfiguration Algorithm with Shockwave Dynamic Compensation Features
Shock and Vibration, 2022 This paper proposes a regularized generalized orthogonal matching pursuit algorithm with dynamic compensation characteristics based on the application context of compressive sensing in shock wave signal testing. We add dynamic compensation denoising as a
Mingchi Ju +5 more
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Signal Reconstruction From Modulo Observations [PDF]
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2019 We consider the problem of reconstructing a signal from under-determined modulo observations (or measurements). This observation model is inspired by a (relatively) less well-known imaging mechanism called modulo imaging, which can be used to extend the dynamic range of imaging systems; variations of this model have also been studied under the category
Shah, Viraj, Hegde, Chinmay
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Reconstructing Boolean Models of Signaling [PDF]
Journal of Computational Biology, 2012 Since the first emergence of protein-protein interaction networks more than a decade ago, they have been viewed as static scaffolds of the signaling-regulatory events taking place in cells, and their analysis has been mainly confined to topological aspects.
Roded, Sharan, Richard M, Karp
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Augmenting Signaling Pathway Reconstructions [PDF]
Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, 2020 AbstractSignaling pathways drive cellular response, and understanding such pathways is fundamental to molecular systems biology. A mounting volume of experimental protein interaction data has motivated the development of algorithms to computationally reconstruct signaling pathways.
Tobias Rubel, Anna Ritz
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