Results 51 to 60 of about 168,598 (259)

Physical-Layer Security Enhancement for UAV Downlink Communication Using Joint Precoding and Artificial Noise Design in Generalized Spatial Directional Modulation

Drones
This paper proposes a novel joint precoding and artificial noise design framework for generalized spatial directional modulation (AN-GSDM) in unmanned aerial vehicle (UAV) communications, aimed at enhancing the physical-layer security of downlink UAV ...
Xianglu Li, Youyang Xiang, Jie Zhou, Ying Luo, Qilong Du, Dong Hou, Jie Tian   +6 more
doaj   +1 more source

On physical‐layer security for primary system in underlay cognitive radio networks

IET Networks, 2018
In this study, the authors consider the physical‐layer security for transmission in underlay cognitive radio networks, where consisting of a primary source–destination pair, a secondary transmitter–receiver pair and a common eavesdropper (E). To transmit
Ping Xie, Moli Zhang, Gaoyuan Zhang, Ruijuan Zheng, Ling Xing, Qingtao Wu   +5 more
doaj   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Secure Hybrid Digital and Analog Precoder for mmWave Systems With Low-Resolution DACs and Finite-Quantized Phase Shifters

IEEE Access, 2019
Millimeter wave (mmWave) communication has been regarded as one of the most promising technologies for the future generation wireless networks because of its advantages of providing a ultra-wide new spectrum and ultra-high data transmission rate.
Ling Xu, Linlin Sun, Guiyang Xia, Tingting Liu, Feng Shu, Yijin Zhang, Jiangzhou Wang   +6 more
doaj   +1 more source

Differentiating noise and modulators in artificial neural networks [PDF]

, 1993
Research in Computational Neural Networks is currently taking place at many different levels; from coarse-grain symbolic models to fine-grain representations of neurons and cell processes. One feature that the different approaches share, is that they are all in relative infancy.
openaire   +2 more sources

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

Robust Synthesis Scheme for Secure Multi-Beam Directional Modulation in Broadcasting Systems

IEEE Access, 2016
Recently, directional modulation has become an active research area in wireless communications due to its security. Unlike existing research work, we consider a multi-beam directional modulation (MBDM) scenario with imperfect desired direction knowledge.
Feng Shu, Xiaomin Wu, Jun Li, Riqing Chen, Branka Vucetic   +4 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

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Oxygen‐Tunnel Indium Tin Oxide Vertical Channel Transistors with Enhanced Current Density and Reliability for Monolithic 3D Compute‐In‐Memory Systems

Advanced Functional Materials, EarlyView.
Oxygen‐tunnel (OT) indium tin oxide (ITO) vertical channel transistors (VCTs) enable reliable, high‐density gain‐cell memory for monolithic 3D integration. A sandwiched SiN/SiO2/SiN OT stack selectively regulates oxygen transport, suppressing parasitic electrode oxidation while stabilizing channel oxygen vacancies, thereby suppressing carrier injection
Hyeonho Gu, Haksoon Jung, Yongwoo Lee, Hoichang Jeong, Yanfeng Zhao, Heesoo Yang, Minho Park, Hyeonjin Lee, Seunghun Baek, Minju Song, Junghwan Kim, Youngmin Jo, Hyunjin Park, Munhyeon Kim, Jae‐Joon Kim, Kyuho Jason Lee, Byungjo Kim, Jimin Kwon   +17 more
wiley   +1 more source