Results 91 to 100 of about 139,689 (265)

Three-dimensional sparse recovery space-time adaptive processing for airborne radar

The Journal of Engineering, 2019
Conventional 3-dimensional (3D) space-time adaptive processing (STAP) has achieved good performance for non-stationary clutter suppression. However, the performance of 3D STAP rapidly degrades when applied to heterogeneous clutter environment due to the ...
Keqing Duan, Hong Xu, Huadong Yuan, Wenchong Xie, Yongliang Wang   +4 more
doaj   +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

Sparse Matching Filtering Algorithm for Tomographic SAR Imaging

Leida xuebao
Synthetic Aperture Radar Tomography (TomoSAR) has emerged as the primary technique for generating 3D SAR point clouds. In practice, ignoring the quadratic phase distribution in the elevation dimension causes defocusing artifacts due to inherent Fresnel ...
Hui LIU, Chunmeng ZHAO, Pengfei CHEN, Yanzhi WANG, Minghao QU, Ning XIAO   +5 more
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

Adaptive Sparse Transform for Wireless Sensor Network Data

Dianxin kexue, 2013
Aiming at the change of sparse structure introduced by mobility of the wireless sensor network（WSN） nodes and noise in data transmission, an adaptive sparse transform method based on dictionary learning （DL）for WSN data was proposed.
Xuan Chen
doaj   +2 more sources

Deep Neural Network Structured Sparse Coding for Online Processing

IEEE Access, 2018
Sparse coding, which aims at finding appropriate sparse representations of data with an overcomplete dictionary set, has become a mature class of methods with good efficiency in various areas, but it faces limitations in immediate processing such as real-
Haoli Zhao, Shuxue Ding, Xiang Li, Huakun Huang   +3 more
doaj   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

MIMO High Frequency Surface Wave Radar Using Sparse Frequency FMCW Signals

International Journal of Antennas and Propagation, 2017
The heavily congested radio frequency environment severely limits the signal bandwidth of the high frequency surface wave radar (HFSWR). Based on the concept of multiple-input multiple-output (MIMO) radar, we propose a MIMO sparse frequency HFSWR system ...
Mengguan Pan, Baixiao Chen
doaj   +1 more source

Sparse Signal Processing Concepts for Efficient 5G System Design

IEEE Access, 2015
As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges, and what are the key drivers is part of ...
Gerhard Wunder, Holger Boche, Thomas Strohmer, Peter Jung   +3 more
doaj   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source