Detail publikace

Behavioral Model for Simplified Identification of Memristor Parameters

Originální název

Behavioral Model for Simplified Identification of Memristor Parameters

Anglický název

Behavioral Model for Simplified Identification of Memristor Parameters

Jazyk

en

Originální abstrakt

The paper deals with a simplified model of the HP TiO2 memristor, which can be used for identifying the parameters of built-in memristors, i.e. in cases where there is only a limited set of measurements possible. The memristor is excited by a rectangular voltage waveform and the built-in measuring device can measure the times when the memristor current crosses several thresholds. The proposed approach is based on deriving a behavioral model being able to reproduce nonlinear dynamics of memristor. The identified parameters may serve to assess process variations and detecting non-catastrophic failures.

Anglický abstrakt

The paper deals with a simplified model of the HP TiO2 memristor, which can be used for identifying the parameters of built-in memristors, i.e. in cases where there is only a limited set of measurements possible. The memristor is excited by a rectangular voltage waveform and the built-in measuring device can measure the times when the memristor current crosses several thresholds. The proposed approach is based on deriving a behavioral model being able to reproduce nonlinear dynamics of memristor. The identified parameters may serve to assess process variations and detecting non-catastrophic failures.

BibTex


@inproceedings{BUT118156,
  author="Zdeněk {Kolka} and Viera {Biolková} and Dalibor {Biolek} and Jiří {Vávra}",
  title="Behavioral Model for Simplified Identification of Memristor Parameters",
  annote="The paper deals with a simplified model of the HP TiO2 memristor, which can be used for identifying the parameters of built-in memristors, i.e. in cases where there is only a limited set of measurements possible. The memristor is excited by a rectangular voltage waveform and the built-in measuring device can measure the times when the memristor current crosses several thresholds. The proposed approach is based on deriving a behavioral model being able to reproduce nonlinear dynamics of memristor. The identified parameters may serve to assess process variations and detecting non-catastrophic failures.",
  address="International Neural Network Society",
  booktitle="Proceedings of 2015 International Joint Conference on Neural Networks (IJCNN 2015)",
  chapter="118156",
  doi="10.1109/IJCNN.2015.7280508",
  howpublished="electronic, physical medium",
  institution="International Neural Network Society",
  year="2015",
  month="july",
  pages="1--4",
  publisher="International Neural Network Society",
  type="conference paper"
}