A Generative Neural Network for Filter Tuning
A generative neural network (GTNN) is presented for microwave filter tuning, consisting of two steps. The first step involves offline modeling, where the physics mechanism of the microwave filter is combined with a shared weight neural network. In the second step, online tuning is performed, and tuning values are generated using a gradient descent method. The experimental results of three different filters illustrate that the GTNN achieves better tuning results, and the tuning value is generated in less than 16 s.
Authors
- Qiangqiang Lin (ORCID: https://orcid.org/0000-0003-3037-5711)
- Jinzhu Zhou (ORCID: https://orcid.org/0000-0002-5930-3044)
- Yongji Ma (ORCID: https://orcid.org/0000-0003-2639-0521)
- Guozhuang Fan
Institutions
- Xidian University (CN)
Publication Details
- Journal
- IEEE Microwave and Wireless Technology Letters
- Published
- 2025-04-22
- DOI
- https://doi.org/10.1109/lmwt.2025.3557834
- Citations
- 1
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China
- Natural Science Basic Research Program of Shaanxi Province