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Determining RF MEMS switch parameter by neural networks
conference contribution
posted on 2009-01-01, 00:00 authored by Y Mafinejad, Abbas KouzaniAbbas Kouzani, K MafinezhadA challenge in designing a RF MEMS switch is the determination of its parameters to satisfy the application requirements. Often this is done through a set of comprehensive time consuming simulations. This paper employs neural networks and develops a supervised learner that is capable of determining S11 parameter for a RF MEMS shunt switch. The inputs are the length its L and the height of its gap. The outputs are S11s for eight different frequency points from 0 to V band. The developed learner helps prevent repetitive simulations when designing the specified switch. Simulation results are presented.
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Event
IEEE Region 10 Conference (2009 : Singapore)Pagination
1 - 5Publisher
IEEELocation
SingaporePlace of publication
Piscataway, N. J.Publisher DOI
Start date
2009-11-23End date
2009-11-26ISBN-13
9781424445462Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2009, IEEETitle of proceedings
TENCON 2009 : Proceedings of the 2009 IEEE Region 10 ConferenceUsage metrics
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