Dynamic Behavior Modeling of Analog Circuits Based on Deep Operator Network

Jinling Zhang*, Shaowei Chen, Yuhan Chen, Yigong Zhang, Shuai Zhao

*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

Abstract

Analog circuits are widely used in audio amplification, computing, power amplification, radio communication, etc. It is crucial to design a reliable circuit health monitoring system. Neural networks (NNs) are general-purpose approximators of continuous functions, however, a little-known but powerful finding is that a neural network with a single hidden layer can accurately approximate any nonlinear continuous operator. The general approximation theorem for operators extends point-topoint mapping to function-to-function mapping, forming the deep operator network (DeepONet). The zero-state response of an analog electrical circuit is equivalent to a convolution operator. This paper aims to use DeepONet to model the physical dynamic behavior of the second-order band-pass filter analog circuit, complete the function mapping from the input end (excitation) to the output end (zero-state response) of the circuit, and then learn the entire filtering function of the circuit. After the network model is trained, we can obtain the output function value of any time point of the circuit for any input of the circuit, to achieve real-time monitoring of the circuit, which is of great significance for improving the system reliability.

OriginalsprogEngelsk
Titel2023 IEEE 2nd Industrial Electronics Society Annual On-Line Conference, ONCON 2023
ForlagIEEE
Publikationsdato2023
Artikelnummer10430836
ISBN (Trykt)979-8-3503-5798-1
ISBN (Elektronisk)979-8-3503-5797-4
DOI
StatusUdgivet - 2023
Begivenhed2nd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2023 - Virtual, Online, USA
Varighed: 8 dec. 202310 dec. 2023

Konference

Konference2nd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2023
Land/OmrådeUSA
ByVirtual, Online
Periode08/12/202310/12/2023

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© 2023 IEEE.

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