Data-Driven Parameter Estimation of Lumped-Element Models via Automatic Differentiation
Alessandro Ilic Mezza,
Riccardo Giampiccolo,
Alberto Bernardini
Abstract:Lumped-element models (LEMs) provide a compact characterization of numerous real-world physical systems, including electrical, acoustic, and mechanical systems. However, even when the target topology is known, deriving model parameters that approximate a possibly distributed system often requires educated guesses or dedicated optimization routines. This article presents a general framework for the data-driven estimation of lumped parameters using automatic differentiation. Inspired by recent work on physical n… Show more
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