Generation of Multi-Scroll Attractors Without Equilibria Via Piecewise Linear Systems

In this paper we present a new class of dynamical system without equilibria which possesses a multi scroll attractor. It is a piecewise-linear (PWL) system which is simple, stable, displays chaotic behavior and serves as a model for analogous non-linear systems. We test for chaos using the 0-1 Test for Chaos of Ref.12.Comment: Corresponding Author: Eric Campos-Cant\'o

Constructing multiwing attractors from a robust chaotic system with non-hyperbolic equilibrium points

We investigate a three-dimensional (3D) robust chaotic system which only holds two nonhyperbolic equilibrium points, and finds the complex dynamical behaviour of position modulation beyond amplitude modulation. To extend the application of this chaotic system, we initiate a novel methodology to construct multiwing chaotic attractors by modifying the position and amplitude parameters. Moreover, the signal amplitude, range and distance of the generated multiwings can be easily adjusted by using the control parameters, which enable us to enhance the potential application in chaotic cryptography and secure communication. The effectiveness of the theoretical analyses is confirmed by numerical simulations. Particularly, the multiwing attractor is physically realized by using DSP (digital signal processor) chip

Attractors and bifurcations of chaotic systems

The hidden bifurcation idea was discovered by the core idea of the Leonov and Kuznetsov method for searching hidden attractors (i.e., homotopy and numerical continuation) differently in order to uncover hidden bifurcations governed by a homotopy parameter ɛ while keeping the numbers of spirals. This idea was first discovered by Menacer et al. In 2016, in the multispiral Chua system, The first part of this thesis is devoted to providing a basic understanding of dynamic systems and chaos, followed by an introduction to the hidden attractors, history, and definitions. An effective procedure for the numerical localization of hidden attractors in multidimensional dynamical systems has been presented by Leonov et Kuznetsov. In this part, we end with the study of hidden attractors in the Chua system. The second part of the analysis consists of first, hidden modalities ofspirals of chaotic attractor via saturated function series and numerical results. Before reaching the asymptotic attractor which possesses an even number of spirals, these latter are generated one after one until they reach their maximum number, matching the value fixed by ɛ. Then, we end up by symmetries in hidden bifurcation routes to multiscroll chaotic attractors generated by saturated function series. The method to find such hidden bifurcation routes (HBR) depends upon two parameters

Novel 3-Scroll Chua’s Attractor with One Saddle-Focus and Two Stable Node-Foci

With new three-segment piecewise-linearity in the classic Chua’s system, two new types of 2-scroll and 3-scroll Chua’s attractors are found in this paper. By changing the outer segment slope of the three-segment piecewise-linearity as positive, the new 2-scroll Chua’s attractor has emerged from one zero index-1 saddle-focus and two symmetric stable nonzero node-foci. In particular, by newly introducing a piecewise-linear control function, an improved Chua’s system only with one zero index-2 saddle-focus and two stable nonzero node-foci is constructed, from which a 3-scroll Chua’s attractor is converged. Some remarks for Chua’s nonlinearities and the generating chaotic attractors are discussed, and the stabilities at the three equilibrium points are then analyzed, upon which the emerging mechanisms of the novel 2-scroll and 3-scroll Chua’s attractors are explored in depth. Furthermore, an analog electronic circuit built with operational amplifier and analog multiplier is designed and hardware circuit experiments are measured to verify the numerical simulations. These novel 2-scroll and 3-scroll Chua’s attractors reported in this paper are completely different from the classic Chua’s attractors, which will enrich the dynamics of the classic Chua’s system

A Novel Highly Nonlinear Quadratic System: Impulsive Stabilization, Complexity Analysis, and Circuit Designing

This work introduces a three-dimensional, highly nonlinear quadratic oscillator with no linear terms in its equations. Most of the quadratic ordinary differential equations (ODEs) such as Chen, Rossler, and Lorenz have at least one linear term in their equations. Very few quadratic systems have been introduced and all of their terms are nonlinear. Considering this point, a new quadratic system with no linear term is introduced. This oscillator is analyzed by mathematical tools such as bifurcation and Lyapunov exponent diagrams. It is revealed that this system can generate different behaviors such as limit cycle, torus, and chaos for its different parameters' sets. Besides, the basins of attractions for this system are investigated. As a result, it is revealed that this system's attractor is self-excited. In addition, the analog circuit of this oscillator is designed and analyzed to assess the feasibility of the system's chaotic solution. The PSpice simulations confirm the theoretical analysis. The oscillator's time series complexity is also investigated using sample entropy. It is revealed that this system can generate dynamics with different sample entropies by changing parameters. Finally, impulsive control is applied to the system to represent a possible solution for stabilizing the system

A Triple-Memristor Hopfield Neural Network With Space Multi-Structure Attractors And Space Initial-Offset Behaviors

© 2023 IEEE. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1109/TCAD.2023.3287760Memristors have recently demonstrated great promise in constructing memristive neural networks with complex dynamics. This paper proposes a memristive Hopfield neural network with three memristive coupling synaptic weights. The complex dynamical behaviors of the triple-memristor Hopfield neural network (TM-HNN), which have never been observed in previous Hopfield-type neural networks, include space multi-structure chaotic attractors and space initial-offset coexisting behaviors. Bifurcation diagrams, Lyapunov exponents, phase portraits, Poincaré maps, and basins of attraction are used to reveal and examine the specific dynamics. Theoretical analysis and numerical simulation show that the number of space multi-structure attractors can be adjusted by changing the control parameters of the memristors, and the position of space coexisting attractors can be changed by switching the initial states of the memristors. Extreme multistability emerges as a result of the TM-HNN’s unique dynamical behaviors, making it more suitable for applications based on chaos. Moreover, a digital hardware platform is developed and the space multi-structure attractors as well as the space coexisting attractors are experimentally demonstrated. Finally, we design a pseudo-random number generator to explore the potential application of the proposed TM-HNN.Peer reviewe

Generating n-Scroll Chaotic Attractors From A Memristor-based Magnetized Hopfield Neural Network

© 2023 IEEE. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1109/TCSII.2022.3212394This brief presents a novel method to generate n-scroll chaotic attractors. First, a magnetized Hopfield neural network (HNN) with three neurons is modeled by introducing an improved multi-piecewise memristor to describe the effect of electromagnetic induction. Theoretical analysis and numerical simulation show that the memristor-based magnetized HNN can generate multi-scroll chaotic attractors with arbitrary number of scrolls. The number of scrolls can be easily changed by adjusting the memristor control parameters. Besides, complex initial offset boosting behavior is revealed from the magnetized HNN. Finally, a magnetized HNN circuit is designed and various typical attractors are verified.Peer reviewe