微波波导放大器的神经网络增强优化

Zhaokai Wang, Jiantao Qu, Yang Gao
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引用次数: 0

摘要

高q波导谐振器越来越普遍,因为平面电路的损耗在更高的频率下是显著的。在放大器设计中,三维波导腔常被用作包括晶体管在内的平面电路的匹配网络。因此,波导到微带转换的互连和晶体管本身的反馈使得物理模型的计算和优化更加困难。神经网络技术可用于波导放大器的电磁优化,提高了设计效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural Network Enhanced Optimization of the Microwave Waveguide Amplifiers
High-Q waveguide resonators have become more commonplace since the losses of planar circuit are significant at higher frequencies. In amplifiers design, three-dimensional (3D) waveguide cavities are often employed as the matching networks of the planar circuits including the transistor. Thus, the interconnection of the waveguide-to-microstrip transition and the feedback of the transistor itself make the calculation and optimization of the physical model more difficult. The neural network technique can be used in the electromagnetic (EM) optimization of the waveguide amplifiers, leading to improved design efficiency.
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