MEMRISTORS 2025

Stanford Model Parameter Fitting Of Experimental I-V Curves Using A Genetic Algorithm

  • Maldonado, David (Universidad Rey Juan Carlos)
  • Cantudo, Antonio (Universidad de Granada)
  • Bargallo, Mireia (Institut de Microelectronica de Barcelona)
  • Campabadal, Francesca (Institut de Microelectronica de Barcelona)
  • Jimenez Molinos, Francisco (Universidad de Granada)
  • Roldan, Juan Bautista (Universidad de Granada)

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Since its introduction, the Stanford model has been one of the most widely adopted memristor models. Including the effect of the series resistance, the model features nine parameters that can be tuned to reproduce experimental results. However, manual fitting of these parameters is often tedious and imprecise.