On the validity of memristor modeling in the neural network literature.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date:

Abstract

An analysis of the literature shows that there are two types of non-memristive models that have been widely used in the modeling of so-called "memristive" neural networks. Here, we demonstrate that such models have nothing in common with the concept of memristive elements: they describe either non-linear resistors or certain bi-state systems, which all are devices without memory. Therefore, the results presented in a significant number of publications are at least questionable, if not completely irrelevant to the actual field of memristive neural networks.

Authors

  • Yuriy V Pershin
    Department of Physics and Astronomy, University of South Carolina, Columbia, SC 29208, USA. Electronic address: pershin@physics.sc.edu.
  • Massimiliano Di Ventra