Results 51 to 60 of about 7,858,197 (288)
IEEE AccessSuppressing random noise and improving the signal-to-noise ratio of seismic data holds immense significance for subsequent high-precision processing. As one of the most widely used denoising methods, self-learning-based algorithms typically partition the
Jian Gao +4 more
doaj +1 more source
Unsupervised Seismic Random Noise Suppression Based on Local Similarity and Replacement Strategy
IEEE Access, 2023 Improving the signal-to-noise ratio and suppressing random noise in seismic data is critical for high-precision processing. Although deep learning-based algorithms have gained popularity as denoising methods, they suffer from poor generalization ability,
Jian Gao +4 more
doaj +1 more source
Revealing the structure of land plant photosystem II: the journey from negative‐stain EM to cryo‐EM
FEBS Letters, EarlyView.Advances in cryo‐EM have revealed the detailed structure of Photosystem II, a key protein complex driving photosynthesis. This review traces the journey from early low‐resolution images to high‐resolution models, highlighting how these discoveries deepen our understanding of light harvesting and energy conversion in plants.
Roman Kouřil
wiley +1 more source
Automatic Gaussian random-noise limiter [PDF]
, 1969 Circuit limits the positive and negative peaks of a random-noise signal. It accurately establishes a known limiting level relative to any given RMS value of the random-noise signal ...
Woodbury, R. C.
core +1 more source
Randomized Benchmarking with Confidence
, 2014 Randomized benchmarking is a promising tool for characterizing the noise in experimental implementations of quantum systems. In this paper, we prove that the estimates produced by randomized benchmarking (both standard and interleaved) for arbitrary ...
Flammia, Steven T., Wallman, Joel J.
core +1 more source
AAA+ protein unfoldases—the Moirai of the proteome
FEBS Letters, EarlyView.AAA+ unfoldases are essential molecular motors that power protein degradation and disaggregation. This review integrates recent cryo‐electron microscopy (cryo‐EM) structures and single‐molecule biophysical data to reconcile competing models of substrate translocation.
Stavros Azinas, Marta Carroni
wiley +1 more source
Unsupervised Seismic Random Noise Attenuation Based on Deep Convolutional Neural Network
IEEE Access, 2019 Random noise attenuation is one of the most essential steps in seismic signal processing. We propose a novel approach to attenuate seismic random noise based on deep convolutional neural network (CNN) in an unsupervised learning manner.
Mi Zhang, Yang Liu, Yangkang Zhang
semanticscholar +1 more source
Enhancing quantum entropy in vacuum-based quantum random number generator
, 2018 Information-theoretically provable unique true random numbers, which cannot be correlated or controlled by an attacker, can be generated based on quantum measurement of vacuum state and universal-hashing randomness extraction.
Cheng, Chen +5 more
core +1 more source
Absolute negative mobility induced by white Poissonian noise [PDF]
, 2013 We research the transport properties of inertial Brownian particles which move in a symmetric periodic potential and are subjected to both a symmetric, unbiased time-periodic external force and biased Poissonian white shot noise (of non-zero average F ...
Hanggi, P., Luczka, J., Spiechowicz, J.
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Molecular Oncology, EarlyView.Nanosecond infrared laser (NIRL) low‐volume sampling combined with shotgun lipidomics uncovers distinct lipidome alterations in oropharyngeal squamous cell carcinoma (OPSCC) of the palatine tonsil. Several lipid species consistently differentiate tumor from healthy tissue, highlighting their potential as diagnostic markers.
Leonard Kerkhoff +11 more
wiley +1 more source