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A large-signal characterization of an HEMT using a multilayered neural network

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4 Author(s)
K. Shirakawa ; Fujitsu Labs. Ltd., Kawasaki, Japan ; M. Shimiz ; N. Okubo ; Y. Daido

We propose an approach to describe the large-signal behavior of a high electron-mobility transistor (HEMT) by using a multilayered neural network. To conveniently implement this in standard circuit simulators, we extracted the HEMT's bias dependent behavior in terms of conventional small-signal equivalent-circuit elements. We successfully represented seven intrinsic elements with a five-layered neural network (composed of 28 neurons) whose inputs are the gate-to source bias (Vgs,) and drain-to-source bias (Vds) A “well-trained” neural network shows excellent accuracy and generates good extrapolations

Published in:

IEEE Transactions on Microwave Theory and Techniques  (Volume:45 ,  Issue: 9 )