Machine Learning Based Approach to Accurately Model and Optimize Microwave Filters
Karimov A. Husain S. Kassymbek M. Hashmi M.
2024Institute of Electrical and Electronics Engineers Inc.
International Conference on Engineering and Emerging Technologies, ICEET
2024Issue 2024
Lately, Artificial Neural Networks (ANNs) have been heavily used for radio frequency and microwave circuits and devices modelling. In this context, ANN based models are developed and assessed in this paper for the modelling and optimization of microwave filters. Four filter designs namely Low-Pass Filter (LPF), High-Pass Filter (HPF), Band-Pass Filter (BPF) and Band-Stop Filter (BSF) are developed and fabricated. The obtained S-parameters behaviors for a broad 0-10 GHz frequency spectrum are analyzed and simulated using ANNs. The developed models demonstrate excellent simulation accuracy, and regression score (R2) more than 99 % for all the filter designs
- Artificial Neural Network (ANN) , Band-Pass Filter (BPF) , Band-Stop Filter (BSF) , High-Pass Filter (HPF) , Low-Pass Filter (LPF) , microwave filter optimization
Text of the article Перейти на текст статьи
School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan
School of Engineering and Digital Sciences
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026