562 citations
- Bulgarian Academy of SciencesBG49 papers
- Chinese Academy of SciencesCN32 papers
- University of Chinese Academy of SciencesCN17 papers
- Institute for Nuclear Research and Nuclear EnergyBG11 papers
- Sofia University "St. Kliment Ohridski"BG10 papers
- Centre National de la Recherche ScientifiqueFR6 papers
- Institute of Physical ChemistryPL5 papers
- Laboratoire de physique des lasersFR5 papers
- Polish Academy of SciencesPL5 papers
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5 papers · 1 filter
Divertor shaping with neutral baffling as a solution to the tokamak power exhaust challenge
K. Verhaegh, J. R. Harrison, D. Moulton +20
Exhausting power from the hot fusion core to the plasma-facing components is one of the biggest challenges in fusion energy. The MAST Upgrade tokamak uniquely integrates strong con…
Passive Integrated Sensing and Communication Scheme based on RF Fingerprint Information Extraction for Cell-Free RAN
Jingxuan Yu, Fan Zeng, Jiamin Li +4
This paper investigates how to achieve integrated sensing and communication (ISAC) based on a cell-free radio access network (CF-RAN) architecture with a minimum footprint of commu…
Robust Transceiver Design for Covert Integrated Sensing and Communications With Imperfect CSI
Yuchen Zhang, Wanli Ni, Jianquan Wang +4
We propose a robust transceiver design for a covert integrated sensing and communications (ISAC) system with imperfect channel state information (CSI). Considering both bounded and…
A new quantum machine learning algorithm: split hidden quantum Markov model inspired by quantum conditional master equation
Xiao-Yu Li, Qin-Sheng Zhu, Yong Hu +4
The Hidden Quantum Markov Model (HQMM) has significant potential for analyzing time-series data and studying stochastic processes in the quantum domain as an upgrading option with…
Data Augmentation and Classification of Sea-Land Clutter for Over-the-Horizon Radar Using AC-VAEGAN
Xiaoxuan Zhang, Zengfu Wang, Kun Lu +1
In the sea-land clutter classification of sky-wave over-the-horizon-radar (OTHR), the imbalanced and scarce data leads to a poor performance of the deep learning-based classificati…