Results 11 to 20 of about 41,317 (296)
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary In this contribution, we propose a detailed study of interpolation‐based data‐driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer function of the underlying (unknown) model, that is, we analyze frequency‐response data.
Quirin Aumann, Ion Victor Gosea
wiley +1 more source
Kinetic Compressive Sensing [PDF]
2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2017 5 pages, 6 figures, Submitted to the Conference Record of "IEEE Nuclear Science Symposium and Medical Imaging Conference (IEEE NSS-MIC) 2017"
Scipioni Michele +6 more
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Universal compressed sensing [PDF]
2016 IEEE International Symposium on Information Theory (ISIT), 2016 In this paper, the problem of developing universal algorithms for compressed sensing of stochastic processes is studied. First, R nyi's notion of information dimension (ID) is generalized to analog stationary processes. This provides a measure of complexity for such processes and is connected to the number of measurements required for their accurate ...
H. Vincent Poor, Shirin Jalali
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Sensors, 2020 With the widespread application of wireless sensor networks, large-scale systems with high sampling rates are becoming more and more common. The amount of original data generated by the wireless sensor network is very large, and transmitting all the ...
Youtian Qie, Chuangbo Hao, Ping Song
doaj +1 more source
A Task-Driven Invertible Projection Matrix Learning Algorithm for Hyperspectral Compressed Sensing
Remote Sensing, 2021 The high complexity of the reconstruction algorithm is the main bottleneck of the hyperspectral image (HSI) compression technology based on compressed sensing.
Shaofei Dai +3 more
doaj +1 more source
Sensors, 2023 High-definition images covering entire large-scene construction sites are increasingly used for monitoring management. However, the transmission of high-definition images is a huge challenge for construction sites with harsh network conditions and scarce
Tuocheng Zeng +4 more
doaj +1 more source
Deep Compressed Sensing Generation Model for End-to-End Extreme Observation and Reconstruction
Applied Sciences, 2022 Data transmission and storage are inseparable from compression technology. Compressed sensing directly undersamples and reconstructs data at a much lower sampling frequency than Nyquist, which reduces redundant sampling.
Han Diao, Xiaozhu Lin, Chun Fang
doaj +1 more source
Quantization and Compressive Sensing [PDF]
, 2015 35 pages, 20 figures, to appear in Springer book "Compressed Sensing and Its Applications ...
Boufounos, Petros +3 more
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Compressed wavefront sensing [PDF]
Optics Letters, 2014 We report on an algorithm for fast wavefront sensing that incorporates sparse representation for the first time in practice. The partial derivatives of optical wavefronts were sampled sparsely with a Shack-Hartman wavefront sensor (SHWFS) by randomly subsampling the original SHWFS data to as little as 5%.
Ryan P. McNabb +3 more
openaire +3 more sources
Chinese Journal of Magnetic Resonance, 2018 Compressed sensing is widely used in accelerated magnetic resonance imaging (MRI) to reduce scan time. With compressed sensing, high-quality MR images could be acquired and reconstructed with only a small amount of K space data.
CHAI Qing-huan +2 more
doaj +1 more source