DocumentCode :
3024429
Title :
Accurate modeling of low actuation voltage RFMEMS switches using artificial neural networks
Author :
Pak, Amin ; Mafinejad, Yasser ; Kouzani, Abbas ; Nabovati, Hooman ; Mafinezhad, Khalil
Author_Institution :
Sadjad Inst. for Higher Educ., Mashhad, Iran
fYear :
2012
fDate :
20-23 May 2012
Firstpage :
3282
Lastpage :
3284
Abstract :
This paper presents a fast and accurate method for extracting the scattering parameters of a RF MEMS switch by using its essential parameters. A neural network is developed for parametric modeling of the switch. The essential parameters of the switch are analyzed in terms of its return loss and isolation with variation of its geometrical component values. Simulation results show that the proposed approach can be used to accurately model the RF characteristics of RF-MEMS switches. The results show good agreement between the neural network prediction and electromagnetic simulations.
Keywords :
microswitches; neural nets; radiofrequency integrated circuits; RF-MEMS switches; artificial neural networks; electromagnetic simulations; geometrical component values; low actuation voltage; neural network prediction; parameter extraction; scattering parameter; Artificial neural networks; Micromechanical devices; Microswitches; Microwave circuits; Radio frequency;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems (ISCAS), 2012 IEEE International Symposium on
Conference_Location :
Seoul
ISSN :
0271-4302
Print_ISBN :
978-1-4673-0218-0
Type :
conf
DOI :
10.1109/ISCAS.2012.6272026
Filename :
6272026
Link To Document :
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