Memristive excitable cellular automata

TL;DR

This paper introduces a minimalistic memristive cellular automaton model that simulates memristor networks with dynamic links, exploring their complex behaviors and information pathways.

Contribution

It presents a novel cellular automaton model incorporating memristive properties with dynamic links and analyzes their emergent behaviors and information processing capabilities.

Findings

Behavior of automata under various perturbations

Formation of localized excitations and defects

Development of information pathways

Abstract

The memristor is a device whose resistance changes depending on the polarity and magnitude of a voltage applied to the device's terminals. We design a minimalistic model of a regular network of memristors using structurally-dynamic cellular automata. Each cell gets info about states of its closest neighbours via incoming links. A link can be one 'conductive' or 'non-conductive' states. States of every link are updated depending on states of cells the link connects. Every cell of a memristive automaton takes three states: resting, excited (analog of positive polarity) and refractory (analog of negative polarity). A cell updates its state depending on states of its closest neighbours which are connected to the cell via 'conductive' links. We study behaviour of memristive automata in response to point-wise and spatially extended perturbations, structure of localised excitations coupled with topological defects, interfacial mobile excitations and growth of information pathways.