DocumentCode :
2712782
Title :
A fuzzy-neural approach for the characterisation of the active microwave devices
Author :
Karlik, Bekir ; TORPI, Hamid ; Alci, Mustafa
Author_Institution :
Dept. of Comput. Eng, Bahrain Univ., Isa Town, Bahrain
fYear :
2002
fDate :
9-13 Sept. 2002
Firstpage :
114
Lastpage :
117
Abstract :
Artificial neural networks are emerging as a powerful technology for RF and microwave characterization, modeling, and design. A neural modeler helps us to immediately start developing neural models for RF/microwave components and circuits and helps to provide neural models for our simulators. In this study, a novel fuzzy neural network structure is used for behavior of an active microwave device. Here, the device is modeled by a black box whose small signal and noise parameters are evaluated through a fuzzy clustering neural network based upon the fitting of both of these parameters.
Keywords :
curve fitting; fuzzy logic; fuzzy neural nets; microwave transistors; semiconductor device models; semiconductor device noise; RF characterization; RF/microwave components; active microwave device; artificial neural networks; design; fuzzy clustering neural network; fuzzy neural network structure; fuzzy-neural characterisation; microwave characterization; modeling; neural models; noise parameters; parameter fitting; small signal parameters; Artificial neural networks; Automatic logic units; Biological neural networks; Circuit noise; Cost function; Electronic mail; Equivalent circuits; Fuzzy neural networks; Microwave devices; Microwave theory and techniques;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Microwave and Telecommunication Technology, 2002. CriMiCo 2002. 12th International Conference
Print_ISBN :
966-7968-12-X
Type :
conf
DOI :
10.1109/CRMICO.2002.1137168
Filename :
1137168
Link To Document :
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