N.P. de Alcantara Jr. (Brazil)
Microstrips antennas, resonance frequency, neural networks, mobile communications.
This paper uses artificial neural networks (ANN) to compute the resonance frequencies of rectangular micro strip antennas (MSA), used in mobile communications. Perceptron Multi-layers (PML) networks were used, with the Quasi-Newton method proposed by Broyden, Fletcher, Goldfarb and Shanno (BFGS). Due to the nature of the problem, two hundred and fifty networks were trained, and the resonance frequency for each test antenna was calculated by statistical methods. The estimate resonance frequencies for six test antennas were compared with others results obtained by deterministic and ANN based empirical models from the literature, and presented a better agreement with the experimental values.
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