Artificial neural network modeling of electromagnetic interference caused by nonlinear devices inside a metal enclosure

References

• Robinson MP, Turner JD, Thomas DWP, Dawson JF, Ganley MD, Marvin AC, Porter SJ, Benson TM, Christopoulos C. Shielding effectiveness of a rectangular enclosure with a rectangular aperture. Electron. Lett. 1996;32:1559–1560.
   Web of Science ®Google Scholar
• Konefal T, Dawson JF, Marvin AC, Robinson MP, Porter SJ. A fast multiple mode intermediate level circuit model for the prediction of shielding effectiveness of a rectangular box containing a rectangular aperture. IEEE Trans. Electromagn. Compat. 2005;47:678–691.
   Web of Science ®Google Scholar
• Shim J, Kam DG, Kwon JH, Kim J. Circuital modeling and measurement of shielding effectiveness against oblique incident plane wave on apertures in multiple sides of rectangular enclosure. IEEE Trans. Electromagn. Compat. 2010;52:566–577.10.1109/TEMC.2009.2039483
   Web of Science ®Google Scholar
• Nie B-L, Du P-A, Yu Y-T, Shi Z. Study of the shielding properties of enclosures with apertures at higher frequencies using the transmission-line modeling method. IEEE Trans. Electromagn. Compat. 2011;53:73–81.10.1109/TEMC.2010.2047398
   Web of Science ®Google Scholar
• Zhuo Y, Yan H, Zhou H, Yan L. Experimental study on effects of non-linear device on linear component inside a metal cavity. In: International Conference on Microwave and Millimeter Wave Technology (ICMMT). vol. 4, Shenzhen, China; 2012 May. p. 1–3.
   Google Scholar
• Araneo R, Lovat G. Fast mom analysis of the shielding effectiveness of rectangular enclosures with apertures, metal plates, and conducting objects. IEEE Trans. Electromagn. Compat. 2009;51:274–283.10.1109/TEMC.2008.2010456
   Web of Science ®Google Scholar
• Jin J-M, Volakis JL. A finite element–boundary integral formulation for scattering by three-dimensional cavity-backed apertures. IEEE Trans. Antennas Propag. 1991;39:97–104.10.1109/8.64442
   Web of Science ®Google Scholar
• Li M, Nuebel J, Drewniak JL, Dubroff RE, Hubing TH, Van Doren TP. EMI from cavity modes of shielding enclosures – FDTD modeling and measurement. IEEE Trans. Electromagn. Compat. 2000;42:29–38.
   Web of Science ®Google Scholar
• Liu Q-F, Yin W-Y, Mao J-F, Chen Z. Accurate characterization of shielding effectiveness of metallic enclosures with thin wires and thin slots. IEEE Trans. Electromagn. Compat. May 2009;51:293–300.10.1109/TEMC.2008.927942
   Web of Science ®Google Scholar
• Bayram Y, Volakis JL. Hybrid s-parameters for transmission line networks with linear/nonlinear load terminations subject to arbitrary excitations. IEEE Trans. Microwave Theory Tech. 2007;55:941–950.10.1109/TMTT.2007.895642
   Web of Science ®Google Scholar
• Bayram Y. John L. Hybrid S-parameters for analysis of mixed RF-digital circuits subject to external electromagnetic interference. Antennas Propag. Soc. Int. Symp. 2005;3A:308–311.
   Google Scholar
• Tesche FM. Development and use of the BLT equation in the time domain as applied to a coaxial cable. IEEE Trans. Electromagn. Compat. 2007;49:3–11.10.1109/TEMC.2006.888184
   Web of Science ®Google Scholar
• Tesche FM. On the analysis of a transmission line with nonlinear terminations using the time-dependent BLT equation. IEEE Trans. Electromagn. Compat. 2007;49:427–433.10.1109/TEMC.2007.897141
   Web of Science ®Google Scholar
• Cohn M, Degenford JE, Newman BA. Harmonic mixing with an antiparallel diode pair. IEEE Trans. Microwave Theory Tech. 1975;MTT-23:667–673.10.1109/TMTT.1975.1128646
   Web of Science ®Google Scholar
• Zhang Q-J, Gupta KC, Devabhaktuni VK. Artificial neural networks for RF and microwave design – from theory to practice. IEEE Trans. Microwave Theory Tech. 2003;51:1339–1350.
   Web of Science ®Google Scholar
• Mkadem F, Boumaiza S. Physically inspired neural network model for RF power amplifier behavioral modeling and digital predistortion. IEEE Trans. Microwave Theory Tech. 2011;59:913–923.
   Google Scholar
• Bose T, Gupta N. Design of an aperture-coupled microstrip antenna using a hybrid neural network. IET Microwaves Antennas Propag. 2012;6:470–474.10.1049/iet-map.2011.0363
   Web of Science ®Google Scholar
• Panchal G, Ganatra A, Kosta YP, Panchal Devyani. Behaviour analysis of multilayer perceptrons with multiple hidden neurons and hidden layers. Int. J. Comput. Theor. Eng. 2011;3:332–337.
   Google Scholar
• Hush DR, Horne BG. Progress in supervised neural networks. IEEE Signal Process Mag. 1993;10:8–39.10.1109/79.180705
   Web of Science ®Google Scholar
• Hao Y, Wilamowski BM. Levenberg–Marquardt training, The Industrial Electronics Handbook. Available from: eng.auburn.edu.
   Google Scholar
• Wilamowski BM, Hao Y. Improved computation for levenberg–marquardt training. IEEE Trans. Neural Networks. 2010;21:930–937.10.1109/TNN.2010.2045657
   PubMed Web of Science ®Google Scholar