Results 151 to 160 of about 36,871 (305)

Investigation of microseismic signal denoising using an improved wavelet adaptive thresholding method. [PDF]

Sci Rep, 2022
Zhang Z, Ye Y, Luo B, Chen G, Wu M.
europepmc   +1 more source

Field‐Free Spin‐Splitting‐Torque Driven Stochastic Neuron Mimicking the Neuromorphic Imagination for High‐Performance Recognition

Advanced Science, EarlyView.
The human brain's imagination, which enables autonomous driving hazard avoidance by completing missing visual information, relies on Gaussian‐stochastic neuron. We report the altermagnetic RuO2 spintronic neurons integrating field‐free switching and intrinsic Gaussian stochasticity, building an all‐spin ANN for high‐quality image repairing and high ...
Junwei Zeng, Baoshan Cui, Xi Guo, Jiahao Liu, Xiaoyu Feng, Liang Fang, Li Xi, Xiaolong Fan, Xiaoxi Liu, Yang Guo   +9 more
wiley   +1 more source

A Novel ECG Signal Denoising Algorithm Based on Sparrow Search Algorithm for Optimal Variational Modal Decomposition. [PDF]

Entropy (Basel), 2023
Mao J, Li Z, Li S, Li J.
europepmc   +1 more source

Diffusion‐Based Generative Model With Scaffold‐Hopping Strategy Yields Highly Potent Bioactive Molecules

Advanced Science, EarlyView.
SMarT‐Diff introduces a multi‐objective generative paradigm that integrates scaffold hopping with structure‐aware scoring to enable controlled exploration beyond the training distribution. The framework consistently balances drug‐likeness, synthesizes accessibility and bioactivity, yielding chemically diverse candidates with enhanced properties.
Yuwei Yang, Xiaoqing Gong, Shukai Gu, Jing Li, Bo Liu, Yanan Tian, Qianqian Zhang, Xiaojun Yao, Huanxiang Liu   +8 more
wiley   +1 more source

ECG Signal Denoising by Discrete Wavelet Transform

, 2017
<p>The denoising of electrocardiogram (ECG) represents the entry point for the processing of this signal. The widely algorithms for ECG denoising are based on discrete wavelet transform (DWT). In the other side the performances of denoising process
Atman Jbari, Abdennasser Bourouhou, Mounaim Aqil   +2 more
core   +1 more source

Application of Variational Mode Decomposition and Whale Optimization Algorithm to Laser Ultrasonic Signal Denoising. [PDF]

Sensors (Basel), 2022
Mao X, Yang Q, Wang X, Li J.
europepmc   +1 more source

Large‐Scale Growth of Self‐Poled Ferroelectric Rashba Semiconductor α‐GeTe(111) Thin Films: A Crucial Step Towards Future CMOS‐Compatible Ferroelectric Spintronic Devices

Advanced Science, EarlyView.
Ferroelectric Rashba semiconductors promise ultralow‐power devices but lack industry‐quality films. This work demonstrates CMOS‐compatible fabrication of high‐quality α‐GeTe(111) films via magnetron sputtering, enabled by a 5 nm Sb2Te3 seed layer. Structural and ferroelectric analyses show robust, switchable polarization comparable to MBE films, paving
Jules Lagrave, Nicolas Bernier, Thomas Jalabert, Yoann Brûlé, Damien Térébénec, Pierre Meilleur, Hervé Roussel, Jean‐Baptiste Dory, Oussama J. Mouawad, Thibault Chommaux, Cristian Mocuta, Dominique Thiaudière, Laurent Vila, Françoise Hippert, Pierre Noé   +14 more
wiley   +1 more source

Application of translation wavelet transform with new threshold function in pulse wave signal denoising. [PDF]

Technol Health Care, 2023
Zhang J, Geng X, Zhang Y, Yao F, Wang Y, Zhang H.   +5 more
europepmc   +1 more source

Machine Learning‐Driven Prediction of Microplastic Aging Processes and Environmental Risk Assessment Across Multi‐Media Systems

Advanced Science, EarlyView.
This perspective proposes a cohesive machine learning strategy to decode microplastic aging. It advocates for Federated Learning to dismantle global data silos and introduces the TRACE framework (TRansport, Aging, Corona, Ecotoxicity). By integrating physics‐informed modeling with causal discovery, this approach bridges the laboratory‐field gap to ...
Yaping Lyu, Xinran Qiu, Xing Li, Tianhuan Yang, Xuetao Guo, Hao Qiu, Peng Zhang   +6 more
wiley   +1 more source

Multiscale dilated denoising convolution with channel attention mechanism for micro-seismic signal denoising

Journal of Petroleum Exploration and Production Technology
Denoising micro-seismic signals is paramount for ensuring reliable data for localizing mining-related seismic events and analyzing the state of rock masses during mining operations.
Jianxian Cai, Zhijun Duan, Li Wang, Juan Meng, Zhenjing Yao   +4 more
doaj   +1 more source