Publicação: New contributions to the determination of resonance frequencies of rectangular microstrip antennas by neural networks
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This paper uses artificial neural networks (ANN) to compute the resonance frequencies of rectangular microstrip 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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Microstrips antennas, Mobile communications, Neural networks, Resonance frequency, Artificial Neural Network, Broyden, Empirical model, Experimental values, Micro-strips, Perceptron, Quasi-Newton methods, Rectangular-microstrip antennas, Resonance frequencies, Test antenna, Intelligent systems, Microstrip antennas, Microwave antennas, Mobile telecommunication systems, Natural frequencies, Newton-Raphson method, Numerical methods, Wireless networks, Mobile antennas
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Inglês
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Proceedings of the IASTED International Conference on Intelligent Systems and Control, p. 99-104.
