| References: [1] Rebeiz, G.M. (2003). RF MEMS Theory, Design, and Technology. Wiley: New York, USA.
[2] Daneshmand, M. and Mansour, R. R. (2007) Redundancy RF MEMS multiport switches and switch matrices. Journal of Microelectromechanical Systems, 16, 296–303.
[3] Vijay, K.A.J., Varadan, K. and Vinoy, K.J. (2003). RF MEMS and Their Applications. Wiley: Chichester, UK.
[4] Schiavone, G., Desmulliez, M.P. and Walton, A.J. (2014). Integrated magnetic MEMS relays: Status of the technology. Micromachines, 5, 622–653.
[5] DiNardo, S., Farinelli, P., Giacomozzi, F., Mannocchi, G., Marcelli, R., Margesin, B., Mezzanotte, P., Mulloni, V., Russer, P., Sorrentino, R., Vitulli, F. and Vietzorreck, L. (2006) Broadband RFMEMS based SPDT. In: Proceedings of the European Microwave Conference 2006, Manchester, Great Britain.
[6] Zhang, Q.J. and Gupta, K.C. (2000). Neural Networks for RF and Microwave Design. Artech House: Boston, USA.
[7] Lee, Y. and Filipovic, D.S. (2005) Combined full-wave/ANN based modelling of MEMS switches for RF and microwave applications. In: Proceedings of the of IEEE Antennas and Propagation Society International Symposium, Vol. 1a, pp. 85–88.
[8] Mafmejad, Y., Kouzani, A.Z. and Mafinezhad, K. (2009), Jan. 2009 Determining RF MEMS switch parameter by neural networks. In: Proceedings of the of IEEE Region 10 Conference 7’ENCON, pp. 1–5.
[9] Lee, Y., Park, Y., Niu, F. and Filipovic, D. (2005) Artificial neural network based macromodeling approach for two-port RF MEMS resonating structures. IEEE Proceedings of Networking, Sensing and Control., 261–266.
[10] Gong, Y., Zhao, F., Xin, H., Lin, J. and Bai, Q. (2009) Simulation and optimal design for RF MEMS cantilevered beam switch. In: Proceedings of the of International Conference on Future Computer and Communication (FCC ’09), pp. 84–87.
[11] Kim, T., Marinkovic, Z., Markovic, V. and Milijic, M. (2013) Pronie-Ran6ie, L. Vietzorreck. Efficient Modelling of an RF MEMS Capacitive Shunt Switch with Artificial Neural Networks. Proceedings of the of URSI-B International Symposium on Electromagnetic Theory, Hiroshima, Japan, May 2013, p 550-553.
[12] Marinkovic, Z., Aleksic, A. and T. Ciric, O. ProniC-Rancic, V. Markovic, L. Vietzorreck, ANN Based Inverse Modeling of RF MEMS Capacitive Switches, 11th Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services TELSIKS 2013, Nil, Serbia, October 16¬19, 2013, p 366-369.
[13] Marinkovic, Z., Aleksic, A., and Ciric, T., Pronic-Rancic, O., Markovic, V., Vietzorreck, L. Inverse electro-mechanical ANN model of RF MEMS capacitive switches - applicability evaluation, XLX Scientific Conference on Information, Communication and Energy Systems and Technologies - ICEST 2015, Sofia, Bulgaria, June 24-26, 2015, p 157-160.
[14] Marinkovic, Z., Kim, T., Markovic, V., Milijic, M., Pronic-Racic, T.B. and Vietzorreck, L. (2016). Artificial Neural Network Based Design of RF MEMS Capacitive Shunt Switches, Applied Computational Electromagnetics Society Journal, 31, 756–764.
[15] Marinkovic, Z., Markovic, V. and T. Ciric, T., Vietzorreck, O. Pronie-Rancic. (2016). Artificial Neural Networks in RF MEMS Switch Modeling, Facta Universitatis, Series: Electronics and Energetics, 29, 177–191.
[16] Ciric, T., Marinkovic, Z., Pronic-Rancic, V. and Markovic, L. Vietzorreck (2017). Vietzorreck. Ann. Approach for Modeling of Mechanical Characteristics of RF MEMS Capacitive Switches - an Overview, Microwave Review, 23, 25–34.
[17] Ciric, T., Dhuri, R., Marinkovia, Z., Pronic-Rancic, O., Markovic, V., Vietzorreck, L. (2018). Neural Based Lumped Element Model of Capacitive RF MEMS Switches, Frequenz, 72, 11-12, 539-546, November. |
