COMPUTATIONAL MODELING OF MEMRISTOR NETWORKS: INFLUENCE OFCONECTIVITY AND ENVIRONMENTAL CONDITIONS ON THEIR ELECTRICALRESPONSE

Abstract

With the perspective of implementing neuromorphic devices using memristor networks, we present a numerical-computational platform that allows studying their electrical transport properties. It consists of a function that describes the behavior of an individual memristor (which enables the consideration of an experimental case of interest) and a connection diagram between memristors. Using this platform, two-dimensional networks of various sizes are studied,also incorporating environmental effects (such as humidity and temperature). Furthermore, by selecting the electrically accessible ports, the impact of connectivity on the electrical properties of the network is evaluated. The results indicate that, beyond the individual characteristics of the memristors (determined by the particular selected model), the degree of connectivity, the topology of the connections, and the environmental conditions significantly influence the macroscopic electrical response of the networks.

Keywords

• memristor networks
• neuromorphic devices