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Potentials of Machine Learning in Vacuum Electronic Devices Demonstrated by the Design of a Magnetron Injection Gun

  • Published:2021-06 Issue:6 Volume:68 Page:3028-3033
  • ISSN:0018-9383
  • Container-title:IEEE Transactions on Electron Devices
  • language:
  • Short-container-title:IEEE Trans. Electron Devices

Author:

Zhang LiangORCID,Cross Adrian W.

Funder

U.K. Engineering and Physical Sciences Research Council

Science and Technology Facilities Council (STFC), Cockcroft Institute Core, U.K.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Electronic, Optical and Magnetic Materials

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Adaptive design of the magnetron injection gun using constrained multiobjective optimization;Swarm and Evolutionary Computation;2023-12

2. Optimization Design of the Magnetron Injection Gun for the Gyrotron with a Pulsed Magnet;2023 26th International Conference on Electrical Machines and Systems (ICEMS);2023-11-05

3. Automated Design of Broadband Folded-Waveguide Slow-Wave Structures for Traveling-Wave Tubes via Deep Reinforcement Learning;IEEE Transactions on Electron Devices;2023-07

4. High-order Discontinuous Galerkin Method for Vacuum Electron Device Modeling;2023 24th International Vacuum Electronics Conference (IVEC);2023-04-25

5. Adjoint Equations for Beam-Wave Interaction and Optimization of TWT Design;IEEE Transactions on Plasma Science;2022-09
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