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RAIDA, Z.
Original Title
Modeling EM Structures in the Neural Network Toolbox of MATLAB
English Title
Type
Peer-reviewed article not indexed in WoS or Scopus
Original 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. Portions of matlab code illustrate descriptions.
English abstract
Keywords
Feed-forward neural networks, genetic algorithms, planar transmission lines, frequency selective surfaces, microstrip antennas, modeling, optimization methods
Key words in English
Authors
RIV year
2011
Released
01.01.2003
ISBN
1045-9243
Periodical
IEEE ANTENNAS AND PROPAGATION MAGAZINE
Volume
44
Number
6
State
United States of America
Pages from
46
Pages count
22
BibTex
@article{BUT41102, author="Zbyněk {Raida}", title="Modeling EM Structures in the Neural Network Toolbox of MATLAB", journal="IEEE ANTENNAS AND PROPAGATION MAGAZINE", year="2003", volume="44", number="6", pages="22", issn="1045-9243" }