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- W3152125120 abstract "Nowadays, there are many various microwave struc- tures for which their nonlinear models for CAD are necessary. However, in the recent PSpice family programs, only a class of five types of MESFET model is available. In the paper, a way is suggested for modeling miscellaneous microwave structures by exclusive neural networks, or corrective neural networks working attached to an updated analytic model. The accuracy of both procedures is assessed by extracting model parameters in static and dynamic domains: first, an approximation of the AlGaAs/InGaAs/GaAs pHEMT output characteristics is carried out by the corrective neural network; and second, an approxi- mation of the capacitance function of the InGaAs/InP avalanche photodiode is performed by the exclusive neural network. A sequence of analyses is also performed for determining optimal structure of the artificial neural network. I. INTRODUCTION The Sussman-Fort, Hantgan, and Huang (1) model equations can be considered a good compromise between complexity and accuracy. Therefore, they can be used as an appropriate base for a corrective neural network, but both static and dynamic parts of them must be modified in advance for modeling the special microwave elements as pHEMT or varactor. However, the accuracy of the updated model functions is still of a percentage order. To be more precise, using the corrective neural network with the suitably modified analytic model can be an effective and relatively simple way." @default.
- W3152125120 created "2021-04-13" @default.
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- W3152125120 date "2006-01-01" @default.
- W3152125120 modified "2023-09-23" @default.
- W3152125120 title "Accurate Modeling of the Special Microwave Structures Using Artificial Neural Networks" @default.
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