Pattern formation dynamics in a Memristor Cellular Nonlinear Network structure with a numerically stable VO2 memristor model
Research output: Contribution to journal › Review article › Contributed › peer-review
Contributors
Abstract
In this work, we explore pattern formation dynamics across a diffusively coupled Memristor Cellular Nonlinear Network (MCNN), which is composed of identical cells with locally active memristors. We bias the cells on the edge-of-chaos, introduce a systematic design procedure to induce complexity in the array, and extract the element values analytically in a parametric form. In order to enhance the stability and speed of the numerical simulations, we apply a simple variable transformation to a core memristor model while we include the additional effect of parasitic resistors to investigate the locally active dynamics of a VO2 device. We first take a close look at the effect of the linear coupling resistor on pattern formation, and later study how nonlinearly-resistive coupling, based upon tangent hyperbolic law, affect the emergence of complex patterns. Simulation results reveal that a variety of static patterns with different characteristics can emerge across the proposed MCNN.
Details
Original language | English |
---|---|
Article number | SM0807 |
Journal | Japanese journal of applied physics |
Volume | 61 |
Issue number | SM |
Publication status | Published - 1 Oct 2022 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0001-7436-0103/work/172566326 |
---|---|
ORCID | /0000-0002-1236-1300/work/172567151 |
Keywords
ASJC Scopus subject areas
Keywords
- local activity, memristor cellular nonlinear network, memristor modeling, NDR memristor, pattern formation, ternary pattern