Neural Networks in Antennas and Microwaves: A Practical Approach

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01_04_24_35.pdf(619.78 KB)
Date
2001-12
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ORCID
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Mark
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Společnost pro radioelektronické inženýrství
Abstract
Neural networks are electronic systems which can be trained to remember behavior of a modeled structure in given operational points, and which can be used to approximate behavior of the structure out of the training points. These approximation abilities of neural nets are demonstrated on modeling a frequency-selective surface, a microstrip transmission line and a microstrip dipole. Attention is turned to the accuracy and to the efficiency of neural models. The association of neural models and genetic algorithms, which can provide a global design tool, is discussed.
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Keywords
Neural networks, genetic algorithms, planar transmis-sion lines, frequency selective surfaces, microstrip antennas, modeling, optimization
Citation
Radioengineering. 2001, vol. 10, č. 4, s. 24-35. ISSN 1210-2512
http://www.radioeng.cz/fulltexts/2001/01_04_24_35.pdf
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Peer-reviewed
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en
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Creative Commons Attribution 3.0 Unported License
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http://hdl.handle.net/11012/58207
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2001/4
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