Physics‐informed neural network assisted automated design of power amplifier by user defined specifications
Gaurav Bhargava,
Hemant Kumari,
Valeria Vadalà
et al.
Abstract:This article presents a model that can automatically produce a power amplifier's (PA) design parameters, that is, transmission lines (TLs) dimension, from a dataset of user‐specified design goals like gain, efficiency, linearity, and scattering (S‐) parameters. Based on the applied boundary conditions, a synthetic dataset is generated with the best range of design parameters (W and L). This dataset is utilized for training the physics‐informed neural network (PINN) model with user‐specified design goals as inp… Show more
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