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A practical large-signal global modeling simulation of a microwave amplifier using artificial neural network

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2 Author(s)
S. Goasguen ; Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ, USA ; S. M. El-Ghazaly

We present a new technique to obtain large-signal global modeling simulation of a MMIC amplifier. The active device is modeled with a neural network trained with data obtained from a full hydrodynamic model. This neural network describes the nonlinearities of the equivalent circuit parameters of a MESFET implemented in an extended Finite Difference Time Domain (FDTD) mesh. We successfully represented the transistor characteristics with a one-hidden-layer neural network whose inputs are the gate voltage Vgs, and the drain voltage Vds. Small-signal simulation is performed and validated by comparison with HP-Libra. Then, the large signal behavior is obtained, which demonstrates the successful use of artificial neural network (ANN) in the FDTD marching time algorithm

Published in:

IEEE Microwave and Guided Wave Letters  (Volume:10 ,  Issue: 7 )