Detail publikace

Classification of Microwave Planar Filters by Deep Learning

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

Originální název

Classification of Microwave Planar Filters by Deep Learning

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

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

Autoři

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

Vydáno

1. 4. 2022

Nakladatel

Czech Technical University in Prague

Místo

PRAHA

ISSN

1221-2512

Periodikum

Radioengineering

Ročník

31

Číslo

1

Stát

Česká republika

Strany od

69

Strany do

76

Strany počet

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"
}