Results 41 to 50 of about 9,948,343 (299)
Restricted Isometries for Partial Random Circulant Matrices [PDF]
, 2010 In the theory of compressed sensing, restricted isometry analysis has become a standard tool for studying how efficiently a measurement matrix acquires information about sparse and compressible signals.
A. Buchholz +37 more
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Sparse channel fast reconstruction algorithm for OFDM system based on IOC-CSMP
Tongxin xuebao, 2023 A fast reconstruction algorithm based on inner product optimization and sparsity updating constraint was proposed for OFDM system channel estimation when the number of channel paths was unknown.By constructing and updating the selection vector, the inner
Wei CUI +4 more
doaj
Sparsity and incoherence in compressive sampling [PDF]
Inverse Problems, 2007 We consider the problem of reconstructing a sparse signal $x^0\in\R^n$ from a limited number of linear measurements. Given $m$ randomly selected samples of $U x^0$, where $U$ is an orthonormal matrix, we show that $\ell_1$ minimization recovers $x^0$ exactly when the number of measurements exceeds \[ m\geq \mathrm{Const}\cdot ^2(U)\cdot S\cdot\log n, \
Candès, Emmanuel, Romberg, Justin
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Compressive Sampling for Array Cameras [PDF]
SIAM Journal on Imaging Sciences, 2021 While design of high-performance lenses and image sensors has long been the focus of camera development, the size, weight, and power of image data processing components are currently the primary ba...
Xuefei Yan +8 more
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Sample Compression Schemes for VC Classes [PDF]
Journal of the ACM, 2016 Sample compression schemes were defined by Littlestone and Warmuth (1986) as an abstraction of the structure underlying many learning algorithms. Roughly speaking, a sample compression scheme of size k means that given an arbitrary list of labeled examples, one can retain only k of them in a ...
Moran, S., Yehudayoff, A.
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BREAKING THE COHERENCE BARRIER: A NEW THEORY FOR COMPRESSED SENSING
Forum of Mathematics, Sigma, 2017 This paper presents a framework for compressed sensing that bridges a gap between existing theory and the current use of compressed sensing in many real-world applications.
BEN ADCOCK +3 more
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Data reduction in the ITMS system through a data acquisition model with self-adaptive sampling rate [PDF]
, 2008 Long pulse or steady state operation of fusion experiments require data acquisition and processing systems that reduce the volume of data involved. The availability of self-adaptive sampling rate systems and the use of real-time lossless data compression
Barrera +8 more
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A rolling bearing fault detection method based on compressed sensing and a neural network
Mathematical Biosciences and Engineering, 2020 The high sampling frequency of traditional Nyquist sampling theory not only puts greater requirements on the sampling equipment, but also generates a large amount of data, which increases the difficulty of information transmission and storage.
Lu Lu, Jiyou Fei, Ling Yu, Yu Yuan
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Fault Diagnosis of a Propeller Using Sub-Nyquist Sampling and Compressed Sensing
IEEE Access, 2022 The fault diagnosis of rotating machinery is generally performed using methods that employ vibration and sound. These methods are simple and accurate. However, all of these methods measure vibration data on the basis of the sampling theorem.
Yuki Kato
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Compressed Sensing for Tactile Skins
, 2016 Whole body tactile perception via tactile skins offers large benefits for robots in unstructured environments. To fully realize this benefit, tactile systems must support real-time data acquisition over a massive number of tactile sensor elements.
Hollis, Brayden +2 more
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