University of Illinois Urbana-Champaign

Input-to-state stable continuous time recurrent neural networks for transient circuit simulation

Yang, Alan

Content Files
YANG-THESIS-2021.pdf

Permalink

https://hdl.handle.net/2142/113934

Description

Title
Input-to-state stable continuous time recurrent neural networks for transient circuit simulation
Author(s)
Yang, Alan
Issue Date
2021-12-10
Director of Research (if dissertation) or Advisor (if thesis)
  • Rosenbaum, Elyse
  • Raginsky, Maxim
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2022-04-29T21:35:55Z
Keyword(s)
  • Input to state stability
  • neural ODE
  • learning dynamics
  • circuit simulation
  • recurrent neural network
Abstract
This thesis proposes a learning approach for continuous-time recurrent neural network (CTRNN) architectures with zero or one hidden layers that guarantees input-to-state stability (ISS). We propose a model parametrization that guarantees the ISS property with respect to a Lur'e-type ISS Lyapunov function that is learned in conjunction with the model parameters. Our stability constraints impose a physical prior on the learned model, and in some cases improve the convergence of model training. The proposed CTRNN models are used to learn fast-to-simulate transient behavioral models for electronic circuits that can be implemented in the Verilog-A analog behavioral modeling language and simulated in commercial circuit simulators. The proposed CTRNNs are used to learn models of a common-source amplifier and a continuous-time linear equalizer that accurately reproduce the original circuits' behavior when interconnected in circuit configurations not encountered during model training.
Graduation Semester
2021-12
Type of Resource
Thesis
Permalink
http://hdl.handle.net/2142/113934
Copyright and License Information
Copyright 2021 Alan Yang

Owning Collections

Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at Illinois