A fuzzy-neural approach for the characterisation of the active microwave devices


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KARLIK B., Torpi H. , ALCI M.

12th International Crimean Conference on Microwave and Telecommunication Technology, Sevastopol, Ukraine, 9 - 13 September 2002, pp.114-117 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/crmico.2002.1137168
  • City: Sevastopol
  • Country: Ukraine
  • Page Numbers: pp.114-117

Abstract

Artificial Neural Networks are emerging as a powerful technology for RF and microwave characterization, modeling, and design. Neural modeler helps us to immediately start developing neural models for RFhlicrowave 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.

Artificial Neural Networks are emerging as a powerful technology for RF and microwave characterization, modeling, and design. 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.