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- W2119047993 abstract "In this paper we present an approach for nonlinear modeling of GAs pHEMTs suitable for mixer design. We use artificial neural networks to model the DC drain current as well as the intrinsic capacitive core versus the intrinsic gate and drain voltages. The model is extracted from the measured DC current and S-parameters. The approach is validated by the comparison of the model simulations with the corresponding nonlinear measurements." @default.
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- W2119047993 date "2015-10-01" @default.
- W2119047993 modified "2023-09-23" @default.
- W2119047993 title "Neural network modelling of GaAs pHEMTs suitable for millimeter-wave mixer design" @default.
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- W2119047993 doi "https://doi.org/10.1109/inmmic.2015.7330355" @default.
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