Progress In Electromagnetics Research
ISSN: 1070-4698, E-ISSN: 1559-8985
Home | Search | Notification | Authors | Submission | PIERS Home | EM Academy
Home > Vol. 98 > pp. 233-249


By J. P. de Villiers and J. P. Jacobs

Full Article PDF (333 KB)

Gaussian process (GP) regression is proposed as a structured supervised learning alternative to neural networks for the modeling of CPW-fed slot antenna input characteristics. A Gaussian process is a stochastic process and entails the generalization of the Gaussian probability distribution to functions. Standard GP regression is applied to modeling S11 against frequency of a CPW-fed secondresonant slot dipole, while an approximate method for large datasets is applied to an ultrawideband (UWB) slot with U-shaped tuning stub --- a challenging problem given the highly non-linear underlying function that maps tunable geometry variables and frequency to S11/input impedance. Predictions using large test data sets yielded results of an accuracy comparable to the target moment-method-based full-wave simulations, with normalized root mean squared errors of 0.50% for the slot dipole, and below 1.8% for the UWB antenna. The GP methodology has various inherent benefits, including the need to learn only a handful of (hyper) parameters, and training errors that are effectively zero for noise-free observations. GP regression would be eminently suitable for integration in antenna design algorithms as a fast substitute for computationally intensive full-wave analyses.

J. P. de Villiers and J. P. Jacobs, "Gaussian process modeling of CPW-fed slot antennas," Progress In Electromagnetics Research, Vol. 98, 233-249, 2009.

1. Kim, Y., S. Keely, J. Ghosh, and H. Ling, "Application of artificial neural networks to broadband antenna design based on a parametric frequency model," IEEE Trans. Antennas Propagat., Vol. 55, No. 3, 669-674, 2007.

2. Patnaik, A., D. E. Anagnostou, R. K. Mishra, C. G. Christodoulou, and J. C. Lyke, "Applications of neural networks in wireless communications," IEEE Antennas Propagat. Mag., Vol. 46, No. 3, 130-137, 2004.

3. He, Q. Q., Q. Wang, and B. Z. Wang, "Conformal array based on pattern reconfigurable antenna and its artificial neural model," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 1, 99-110, 2008.

4. Rayas-Sanchez, J. E., "EM-based optimization of microwave circuits using artificial neural networks: The state-of-the-art," IEEE Trans. Microw. Theory Tech., Vol. 52, No. 1, 420-435, 2004.

5. Kaya, S., M. Turkmen, K. Guney, and C. Yildiz, "Neural models for the elliptic- and circular-shaped microshield lines," Progress In Electromagnetics Research B, Vol. 6, 169-181, 2008.

6. Yildiz, C. and M. Turkmen, "Quasi-static models based on artificial neural neworks for calculating the characteristic parameters of multilayer cylindrical coplanar waveguide and strip line," Progress In Electromagnetics Research B, Vol. 3, 1-22, 2008.

7. Ayestaran, R. G., F. Las-Heras, and J. A. Martinez, "Non uniform-antenna array synthesis using neural networks," Journal of Electromagnetic Waves and Applications , Vol. 21, No. 8, 1001-1011, 2007.

8. Zainud-Deen, S. H., H. A. El-Azem Malhat, K. H. Awadalla, and E. S. El-Hadad, "Direction of arrival and state of polarization estimation using radial basis function neural network (RBFNN)," Progress In Electromagnetics Research B, Vol. 2, 137-150, 2008.

9. Kizilay, A. and S. Makal, "A neural network solution for identification and classification of cylindrical targets above perfectly conducting flat surfaces," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 14, 2147-2156, 2007.

10. Rostami, A. and A. Yazdanpanah-Goharrizi, "Hybridization of neural networks and genetic algorithms for identification of complex Bragg gratings," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 5-6, 643-664, 2008.

11. Rasmussen, C. E. and C. K. I. Williams, Gaussian Processes for Machine Learning, MIT Press, Cambridge, Massachussets, 2006.

12. Zhang, Q.-J., K. C. Gupta, and V. K. Devabhaktuni, "Artificial neural networks for RF and microwave design --- From theory to practice," IEEE Trans. Microw. Theory Tech., Vol. 51, No. 4, 1339-1350, 2003.

13. Angiulli, G., M. Cacciola, and M. Versaci, "Microwave devices and antennas modelling by support vector regression machines," IEEE Trans. Magnetics, Vol. 43, No. 4, 1589-1592, 2007.

14. Devabhaktuni, V. K., M. C. E. Yagoub, and Q.-J. Zhang, "A robust algorithm for automatic development of neural-network models for microwave applications," IEEE Trans. Microw. Theory Tech., Vol. 49, No. 12, 2282-2291, 2001.

15. MacKay, D. J. C., Information Theory, Inference, and Learning Algorithms, Cambridge University Press, 2003.

16. Qiu, M., M. Simcoe, and G. V. Eleftheriades, "High-gain meanderless slot arrays on electrically thick substrates at millimeter-wave frequencies," IEEE Trans. Microw. Theory Tech., Vol. 50, No. 2, 517-528, 2002.

17. Jacobs, J. P. and J. Joubert, "Design of a linear nonuniform CPW-fed slot array with reduced sidelobe levels," Microw. Opt. Tech. Lett., Vol. 51, No. 9, 2175-2178, 2009.

18. Zeland Software, IE3D Users Manual, Release 14, 2007.

19. Zhang, L., Y. C. Jiao, Y. L. Zhao, G. Zhao, Y. Song, Z. B. Wong, and F. S. Zhang, "Dual-band CPW-fed double H-shaped slot antenna for RFID application," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 8-9, 1050-1055, 2008.

20. Zhang, T. L., Z. H. Yan, L. Chen, and Y. Song, "A compact dual-band CPW-fed planar monopole antenna for WLAN applications," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 14-15, 2097-2104, 2008.

21. Zhang, G. M., J. S. Hong, B. Z. Wang, Q. Y. Qin, J. B. Mo, and D. M. Wan, "A novel multi-folded UBW antenna fed by CPW," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 14, 2109-2119, 2007.

22. Chen, Y.-I., C.-L. Ruan, and L. Peng, "A novel ultra-wideband bow-tie slot antenna in wireless communication systems," Progress In Electromagnetics Research Letters, Vol. 1, 101-108, 2008.

23. Lee, S. H., J. N. Lee, J. K. Park, and H. S. Kim, "Design of the compact UWB antenna with PI-shaped matching stub," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 10, 1440-1449, 2008.

24. Wang, X., Z. F. Yao, Z. Cui, L. Luo, and S. X. Zhang, "Band-notched characteristics for CPW-fed printed monopole antenna with E shape slot," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 16, 2171-2178, 2008.

25. Yao, Z. F., X. Wang, S. G. Zhou, B. H. Sun, and Q. Z. Liu, "Compact ultra-wideband slot antenna with dual band-notched characteristics," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 13, 1765-1774, 2008.

26. Yao, Z. F., S. G. Zhou, X. Wang, L. Sun, B. H. Sun, and Q. Z. Liu, "Study of the band-notched functions for CPW-fed UWB antenna," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 17-18, 2309-2321, 2008.

27. Yin, X.-C., C.-L. Ruan, C.-Y. Ding, and J.-H. Chu, "A planar U type monopole antenna for UWB applications," Progress In Electromagnetics Research Letters, Vol. 2, 1-10, 2008.

28. Chair, R., , A. A. Kisk, and K. F. Lee, "Ultrawide-band coplanar waveguide-fed rectangular slot antenna," IEEE Antennas Wireless Propagat. Lett., Vol. 3, 227-229, 2004.

29. Boyle, P. and M. Frean, "Dependent gaussian processes," Advances in Neural Information Processing Systems, Vol. 17, 217-224, 2005.

30. Jones, D. R., "A taxonomy of global optimization methods based on response surfaces," Journal of Global Optimization, Vol. 21, 345-383, 2001.

© Copyright 2014 EMW Publishing. All Rights Reserved