Pre-Design of Multi-Band Planar Antennas by Artificial Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F24%3A00558955" target="_blank" >RIV/60162694:G43__/24:00558955 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26220/23:PU148289
Result on the web
<a href="https://www.mdpi.com/2079-9292/12/6/1345" target="_blank" >https://www.mdpi.com/2079-9292/12/6/1345</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/electronics12061345" target="_blank" >10.3390/electronics12061345</a>
Alternative languages
Result language
angličtina
Original language name
Pre-Design of Multi-Band Planar Antennas by Artificial Neural Networks
Original language description
In this communication, artificial neural networks are used to estimate the initial structure of a multiband planar antenna. The neural networks are trained on a set of selected normalized multiband antennas characterized by time-efficient modal analysis with limited accuracy. Using the Deep Learning Toolbox in Matlab, several types of neural networks have been created and trained on the sample planar multiband antennas. In the neural network learning process, suitable network types were selected for the design of these antennas. The trained networks, depending on the desired operating bands, will select the appropriate antenna geometry. This is further optimized using Newton's method in HFSS. The use of the neural pre-design concept speeds up and simplifies the design of multiband planar antennas. The findings presented in this paper will be used to refine and accelerate the design of planar multiband antennas.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
ELECTRONICS
ISSN
2079-9292
e-ISSN
2079-9292
Volume of the periodical
12
Issue of the periodical within the volume
6
Country of publishing house
CH - SWITZERLAND
Number of pages
11
Pages from-to
1345
UT code for WoS article
000956815500001
EID of the result in the Scopus database
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