Litcius/Paper detail

Edge of Chaos Is Sine Qua Non for Turing Instability

Alon Ascoli, Ahmet Şamil Demirkol, Ronald Tetzlaff, Leon O. Chua

2022IEEE Transactions on Circuits and Systems I Regular Papers49 citationsDOI

Abstract

Diffusion-driven instabilities with pattern formation may occur in a network of identical, regularly-spaced, and resistively-coupled cells if and only if the uncoupled cell is poised on a locally-active and stable operating point in the Edge of Chaos domain. This manuscript presents the simplest ever-reported two-cell neural network, combining together only 7 two-terminal components, namely 2 batteries, 3 resistors, and 2 volatile NbOx memristive threshold switches from NaMLab, and subject to diffusion-driven instabilities with the concurrent emergence of Turing patterns. Very remarkably, this is the first time an homogeneous cellular medium, with no other dynamic element than 2 locally-active memristors, hence the attribute all-memristor coined to address it in this paper, is found to support complex phenomena. The destabilization of the homogeneous solution occurs in this second-order two-cell array if and only if the uncoupled cell circuit parameters are chosen from the Edge of Chaos domain. A deep circuit- and system-theoretic investigation, including linearization analysis and phase portrait investigation, provides a comprehensive picture for the local and global dynamics of the bio-inspired network, revealing how a theory-assisted approach may guide circuit design with inherently non-linear memristive devices.

Topics & Concepts

Edge of chaosMemristorTuringComputer scienceDomain (mathematical analysis)Cellular neural networkPhase portraitAttractorPhysicsTopology (electrical circuits)Artificial neural networkMathematicsBifurcationElectrical engineeringArtificial intelligenceNonlinear systemMathematical analysisEngineeringQuantum mechanicsProgramming languageAdvanced Memory and Neural ComputingNeural dynamics and brain functionstochastic dynamics and bifurcation