Publication detail

Classification of Microwave Planar Filters by Deep Learning

VESELÝ, J. OLIVOVÁ, J. GÖTTHANS, J. GÖTTHANS, T. RAIDA, Z.

Original Title

Classification of Microwave Planar Filters by Deep Learning

Type

journal article in Web of Science

Language

English

Original Abstract

Over the last few decades, deep learning has been considered to be powerful tool in the classification tasks, and has become popular in many applications due to its capabil-ity of processing huge amount of data. This paper presents approaches for image recognition. We have applied convolu-tional neural networks on microwave planar filters. The first task was filter topology classification, the second task was filter order estimation. For the task a dataset was generated. As presented in the results, the created and trained neural networks are very capable of solving the selected tasks.

Keywords

Convolutional neural network; deep learning; band pass filter; low pass shunt filter; low pass stepped filter; order of filter

Authors

VESELÝ, J.; OLIVOVÁ, J.; GÖTTHANS, J.; GÖTTHANS, T.; RAIDA, Z.

Released

1. 4. 2022

Publisher

Czech Technical University in Prague

Location

PRAHA

ISBN

1221-2512

Periodical

Radioengineering

Year of study

31

Number

1

State

Czech Republic

Pages from

69

Pages to

76

Pages count

8

URL

https://www.radioeng.cz/fulltexts/2022/22_01_0069_0076.pdf

BibTex

@article{BUT178117,
  author="Jiří {Veselý} and Jana {Olivová} and Jakub {Götthans} and Tomáš {Götthans} and Zbyněk {Raida}",
  title="Classification of Microwave Planar Filters by Deep Learning",
  journal="Radioengineering",
  year="2022",
  volume="31",
  number="1",
  pages="69--76",
  doi="10.13164/re.2022.0069",
  issn="1221-2512",
  url="https://www.radioeng.cz/fulltexts/2022/22_01_0069_0076.pdf"
}