Results 61 to 70 of about 181,397 (258)

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 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

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +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

Optimal Transmission With Artificial Noise in MISOME Wiretap Channels [PDF]

IEEE Transactions on Vehicular Technology, 2016
We investigate the optimal physical-layer secure transmission with artificial noise in the wiretap channel with $N$ antennas at the transmitter, a single antenna at the receiver, and $M$ antennas at the eavesdropper. We analyze the performance and determine the optimal transmission parameters for two distinct schemes: 1) an on–off ...
Nan (Jonas) Yang, Maged Elkashlan, Trung Quang Duong, Jinhong Yuan, Robert A. Malaney   +4 more
openaire   +3 more sources

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +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

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

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

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