Reconstructing parameters of the FitzHugh-Nagumo system from boundary potential measurements

Yuan He*, David Elliot Keyes

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

We consider distributed parameter identification problems for the FitzHugh-Nagumo model of electrocardiology. The model describes the evolution of electrical potentials in heart tissues. The mathematical problem is to reconstruct physical parameters of the system through partial knowledge of its solutions on the boundary of the domain. We present a parallel algorithm of Newton-Krylov type that combines Newton's method for numerical optimization with Krylov subspace solvers for the resulting Karush-Kuhn-Tucker system. We show by numerical simulations that parameter reconstruction can be performed from measurements taken on the boundary of the domain only. We discuss the effects of various model parameters on the quality of reconstructions.

Original languageEnglish (US)
Pages (from-to)251-264
Number of pages14
JournalJournal of Computational Neuroscience
Volume23
Issue number2
DOIs
StatePublished - Oct 1 2007

Keywords

  • Electrocardiology
  • FitzHugh-Nagumo model
  • Inverse problems
  • KKTsystem
  • Newton-Krylov method
  • PDE-constrained optimization
  • Parameter identification

ASJC Scopus subject areas

  • Sensory Systems
  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

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