Results 61 to 70 of about 25,250,472 (296)

Noise suppression ability and its mechanism analysis of scale-free spiking neural network under white Gaussian noise.

PLoS ONE, 2020
With the continuous improvement of automation and informatization, the electromagnetic environment has become increasingly complex. Traditional protection methods for electronic systems are facing with serious challenges.
Lei Guo, Enyu Kan, Youxi Wu, Huan Lv, Guizhi Xu   +4 more
doaj   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

On exact special solutions for the stochastic regularized long wave-Burgers equation

Advances in Difference Equations, 2020
In this paper, we will analyze the Regularized Long Wave-Burgers equation with conformable derivative (cd). Some white noise functional solutions for this equation are obtained by using white noise analysis, Hermite transforms, and the modified sub ...
Zeliha Korpinar, Mustafa Inc, Ali S. Alshomrani, Dumitru Baleanu   +3 more
doaj   +1 more source

A Numerical–Experimental Approach for Multi‐Matrix Fiber‐Reinforced Plastics Characterization Using Finite Element Model Updating

Advanced Engineering Materials, EarlyView.
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora, Tales V. Lisbôa, Axel Spickenheuer, Rogério J. Marczak, Jakson M. Vassoler   +4 more
wiley   +1 more source

Force feedback linearization for higher-order electromechanical sigma-delta modulators.

, 2005
A higher-order electromechanical sigma–delta modulator can greatly improve the signal-to-noise ratio compared with a second-order loop that only uses the sensing element as a loop filter.
Redman-White, William, Dong, Yufeng, Kraft, Michael   +2 more
core   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Digital Signal Extraction by Means of Nonlinear Stochastic Filtration

Vìsnik Nacìonalʹnogo Tehnìčnogo Unìversitetu Ukraïni Kììvsʹkij Polìtehnìčnij Ìnstitut: Serìâ Radìotehnìka, Radìoaparatobuduvannâ, 2018
The results of noise immunity analysis for digital communication systems using methods of nonlinear filtering are given. Nonlinear filtration is based on stochastic resonance effect.
O. I. Kharchenko, V. M. Kartashov
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Clark-Ocone type formulas in the Meixner white noise analysis

Karpatsʹkì Matematičnì Publìkacìï, 2011
Clark-Ocone type formulas in the Meixner white noiseanalysis}%{In the classical Gaussian analysis the Clark-Ocone formula allowsto reconstruct an integrand if we know the It^ostochastic integral.
N. A. Kachanovsky
doaj  

Effects of white noise on preterm infants in the neonatal intensive care unit: A meta‐analysis of randomised controlled trials

Nursing Open
Aim To critically assess the effects of white noise on the pain level, weight gain and vital signs (heart rate, respiratory rate and oxygen saturation) of preterm infants in neonatal intensive care units (NICUs).
Qing Zhang, Qiugui Huo, Peizhen Chen, Wenying Yao, Zhihong Ni   +4 more
doaj   +1 more source