Neural Networks in Antennas and Microwaves: A Practical Approach
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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.
KeywordsNeural networks, genetic algorithms, planar transmis-sion lines, frequency selective surfaces, microstrip antennas, modeling, optimization
Document typePeer reviewed
Document versionFinal PDF
SourceRadioengineering. 2001, vol. 10, č. 4, s. 24-35. ISSN 1210-2512
- 2001/4