Results 21 to 30 of about 9,228 (164)

On Fields with Finite Information Density [PDF]

, 2004
The existence of a natural ultraviolet cutoff at the Planck scale is widely expected. In a previous Letter, it has been proposed to model this cutoff as an information density bound by utilizing suitably generalized methods from the mathematical theory ...
A. Kempf, A. Kempf, A. Kempf, A. Kempf, A. Kempf, A.I. Zayed, A.I. Zayed, A.J. Jerri, Achim Kempf, C.E. Shannon, D. Amati, D.J. Gross, D.V. Ahluwalia, E. Witten, G. Amelino-Camelia, G. ’t Hooft, H.J. Landau, H.J. Landau, J.D. Bekenstein, M.-J. Jaeckel, M.H. Annaby, M.V. Berry, P.S. Custodio, R. Bousso, Y. Aharonov, Y.I. Lyubarskii   +25 more
core   +1 more source

Tree-Structured Dilated Convolutional Networks for Image Compressed Sensing

IEEE Access, 2022
To better recover a sparse image signal carrying redundant information from many fewer measurements than the Nyquist-Shannon sampling theorem suggested, convolutional neural networks (CNNs) can be used to emulate a compressed sensing (CS) process ...
Rui Lu, Kuntao Ye
doaj   +1 more source

Compressed sensing reconstruction for axial piston pump bearing vibration signals based on adaptive sparse dictionary model

Measurement + Control, 2020
Aiming at the mechanical equipment in the fault diagnosis process, the traditional Shannon–Nyquist sampling theorem is used for data collection, which faces main problems of storage, transmission, and processing of mechanical vibration signals.
Xiao Chaoang, Tang Hesheng, Ren Yan
doaj   +1 more source

Aliasing-Free Nonlinear Signal Processing Using Implicitly Defined Functions

IEEE Access, 2022
Digital signal processing relies on the Nyquist-Shannon sampling theorem that applies to and requires a continuous signal with limited bandwidth. However, many systems or networks of signal processing involve nonlinear functions, which could generate new
Emmy S. Wei
doaj   +1 more source

Speech Compressive Sampling Using Approximate Message Passing and a Markov Chain Prior

Sensors, 2020
By means of compressive sampling (CS), a sparse signal can be efficiently recovered from its far fewer samples than that required by the Nyquist–Shannon sampling theorem.
Xiaoli Jia, Peilin Liu, Sumxin Jiang
doaj   +1 more source

Non-Parametric Simultaneous Reconstruction and Denoising via Sparse and Low-Rank Regularization

Frontiers in Earth Science, 2022
Spatial irregular sampling and random noise are two important factors that restrict the accuracy of seismic imaging. Seismic wavefield reconstruction and denoising based on sparse representation are two popular antidotes to these two inevitable issues ...
Lingjun Meng, Zhanzhan Shi, Zhanzhan Shi, Yan Ye, Yuanjun Wang, Yuanjun Wang   +5 more
doaj   +1 more source

Spectral analysis in determining water quality sampling intervals

RBRH, 2019
To make water quality series more representative, real-time monitoring techniques are developed. However, these techniques have obstacles in their use, such as high costs and difficulties in equipment installation, maintenance, and calibration.
Régis Leandro Lopes da Silva, André Luiz Lopes da Silveira, Geraldo Lopes da Silveira   +2 more
doaj   +1 more source

Overview of Compressed Sensing: Sensing Model, Reconstruction Algorithm, and Its Applications

Applied Sciences, 2020
With the development of intelligent networks such as the Internet of Things, network scales are becoming increasingly larger, and network environments increasingly complex, which brings a great challenge to network communication.
Lixiang Li, Yuan Fang, Liwei Liu, Haipeng Peng, Jürgen Kurths, Yixian Yang   +5 more
doaj   +1 more source

Compressed Sensing-Based MRI Reconstruction Using Complex Double-Density Dual-Tree DWT

International Journal of Biomedical Imaging, 2013
Undersampling k-space data is an efficient way to speed up the magnetic resonance imaging (MRI) process. As a newly developed mathematical framework of signal sampling and recovery, compressed sensing (CS) allows signal acquisition using fewer samples ...
Zangen Zhu, Khan Wahid, Paul Babyn, Ran Yang   +3 more
doaj   +1 more source

Compressive Sensing for Spread Spectrum Receivers [PDF]

, 2013
With the advent of ubiquitous computing there are two design parameters of wireless communication devices that become very important power: efficiency and production cost.
Fyhn, Karsten, Jensen, Søren Holdt, Jensen, Tobias Lindstrøm, Larsen, Torben   +3 more
core   +2 more sources