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.
@article{arxiv.1904.08839,
title = {On the validity of memristor modeling in the neural network literature},
author = {Y. V. Pershin and M. Di Ventra},
journal= {arXiv preprint arXiv:1904.08839},
year = {2019}
}