Determining RF MEMS switch parameter by neural networks
Contribuinte(s) |
[Unknown] |
---|---|
Data(s) |
01/01/2009
|
Resumo |
A 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.<br /> |
Identificador | |
Idioma(s) |
eng |
Publicador |
IEEE |
Relação |
http://dro.deakin.edu.au/eserv/DU:30029258/kouzani-TENCON-2009.pdf http://dro.deakin.edu.au/eserv/DU:30029258/kouzani-TENCONrefereeddetermining-2009.pdf http://dro.deakin.edu.au/eserv/DU:30029258/kouzani-determiningrfmemsswitch-2009.pdf http://dx.doi.org/10.1109/TENCON.2009.5396083 |
Direitos |
2009, IEEE |
Palavras-Chave | #MEMS #RF #switch #neural networks |
Tipo |
Conference Paper |