Analysis of a microwave filter parameters for design optimization via machine learning

被引：0

作者：

Araujo, J. A., I ^{[1
]}

Barboza, Amanda G. ^{[1
]}

Llamas-Garro, Ignacio ^{[2
]}

Cavalcanti Filho, P. H. B. ^{[1
]}

Cavalcanti, Camila da S. ^{[1
]}

Barbosa, D. C. P. ^{[3
]}

de Melo, Marcos Tavares ^{[1
]}

de Oliveira, J. M. A. M. ^{[1
]}

机构：

[1] Univ Fed Pernambuco, Dept Elect & Syst, Recife, PE, Brazil

[2] Ctr Tecnol Telecomunicac Catalunya CTTC CERCA, Castelldefels, Spain

[3] Univ Fed Pernambuco, Elect Engn Dept, Recife, PE, Brazil

来源：

2023 SBMO/IEEE MTT-S INTERNATIONAL MICROWAVE AND OPTOELECTRONICS CONFERENCE, IMOC | 2023年

关键词：

cluster; machine learning; microwave filter; optimization;

D O I：

10.1109/IMOC57131.2023.10379727

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Microwave filters are essential for filtering and selecting frequencies. They prevent interference, enhance signal quality, and maximize the efficiency of microwave systems. They are widely employed in wireless communications, satellites, and radar systems. To optimize the design of these filters, techniques like machine learning can be utilized, saving time and resources compared to simulations. Machine learning learns from data to discover optimized solutions more swiftly and efficiently, leading to high-performance filters. In this work, analyses of the parameters of a T-inverted filter were performed to serve as a foundation for a machine learning-based design. The filter used was designed and manufactured for a frequency range of 1 GHz to 3 GHz and its measured and simulated results were compared as a way of validating the structure.

引用

页码：100 / 102

页数：3

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