Title: Generation of chaotic attractors using neurons with multidentrites

Authors: Salma Ben Mamia; William Puech; Kais Bouallegue

Addresses: Electronics and Microelectronics Laboratory, University of Monastir, Tunisia ' LIRMM, University of Montpellier, CNRS, France ' ISSAT, Higher Institute of Applied Sciences and Technology of Sousse, Tunisia

Abstract: Compared to traditional chaotic systems like Lorenz, Chua, logistic map and Rössler systems, a different generation of new chaotic systems emerged, based on the mathematical model of a variable structure model of neurons (VSMNs). A detailed bifurcation analysis of the new chaotic system with theory and simulations is discussed. Our new discovery has some attractive features valuable for engineering applications, such as security communication. In this paper, we present some types of coupling of our new chaotic system. Using VSMN, the system can generate a single, spiral or double-scroll chaotic attractor. With changing parameters and adding oscillators, their behaviour changes into four symmetric and coexisting double-scroll chaotic attractors. We conclude that coupling with chaotic attractors not only increases the chaos complexity but also generates multi hyperchaotic attractors. Finally, we couple between two chaotic attractors using neurons, which leads to a multi-stability system. They illustrate that our multi-scroll system is hyperchaotic and its complexity can ensure perfect security for telecommunication systems for the future.

Keywords: dendrites; hyperchaotic attractor; neural networks; variable structure model of neuron; VSMN.

DOI: 10.1504/IJMIC.2022.124083

International Journal of Modelling, Identification and Control, 2022 Vol.40 No.1, pp.92 - 104

Received: 25 Jun 2021
Accepted: 05 Dec 2021
Published online: 12 Jul 2022 *

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