Tracking the chaotic behaviour of fractional-order Chua’s system by Mexican hat wavelet-based artificial neural network

In this paper, a process is devised systematically to scrutinize the scrolling chaotic behaviour of fractional-order Chua's system. The process is composed of fractional Laplace transformation, artificial neural network with Mexican hat wavelet as an activation function and simulated annealing....

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Main Authors: Najeeb A Khan, Tooba Hameed, Oyoon A Razzaq, Muhammad Ayaz
Format: Article
Language:English
Published: SAGE Publishing 2019-12-01
Series:Journal of Low Frequency Noise, Vibration and Active Control
Online Access:https://doi.org/10.1177/1461348418813015
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spelling doaj-5ed73aad0d4243a69a96fac55d60fd8d2020-11-25T03:26:26ZengSAGE PublishingJournal of Low Frequency Noise, Vibration and Active Control1461-34842048-40462019-12-013810.1177/1461348418813015Tracking the chaotic behaviour of fractional-order Chua’s system by Mexican hat wavelet-based artificial neural networkNajeeb A KhanTooba HameedOyoon A RazzaqMuhammad AyazIn this paper, a process is devised systematically to scrutinize the scrolling chaotic behaviour of fractional-order Chua's system. The process is composed of fractional Laplace transformation, artificial neural network with Mexican hat wavelet as an activation function and simulated annealing. Sequentially, the parametric expansion of fractional Laplace transform is employed to convert the governing fractional system into an ordinary differential system. Next, artificial neural network and simulated annealing approximate and optimize the attained system and produce accurate solutions. The predictability and elaboration of double scrolling chaotic structures of fractional-order Chua's system are also studied using the Lyapunov exponent and fifth–fourth Runge–Kutta method. Moreover, the mean absolute error and root mean square error are measured for the convergence analysis of the proposed scheme. On the whole, the accurate approximate solutions, the phase plots of Lyapunov exponent spectrum and bifurcation maps of the dynamical evolution of fractional Chua's system are a triumph of this endeavour.https://doi.org/10.1177/1461348418813015
collection DOAJ
language English
format Article
sources DOAJ
author Najeeb A Khan
Tooba Hameed
Oyoon A Razzaq
Muhammad Ayaz
spellingShingle Najeeb A Khan
Tooba Hameed
Oyoon A Razzaq
Muhammad Ayaz
Tracking the chaotic behaviour of fractional-order Chua’s system by Mexican hat wavelet-based artificial neural network
Journal of Low Frequency Noise, Vibration and Active Control
author_facet Najeeb A Khan
Tooba Hameed
Oyoon A Razzaq
Muhammad Ayaz
author_sort Najeeb A Khan
title Tracking the chaotic behaviour of fractional-order Chua’s system by Mexican hat wavelet-based artificial neural network
title_short Tracking the chaotic behaviour of fractional-order Chua’s system by Mexican hat wavelet-based artificial neural network
title_full Tracking the chaotic behaviour of fractional-order Chua’s system by Mexican hat wavelet-based artificial neural network
title_fullStr Tracking the chaotic behaviour of fractional-order Chua’s system by Mexican hat wavelet-based artificial neural network
title_full_unstemmed Tracking the chaotic behaviour of fractional-order Chua’s system by Mexican hat wavelet-based artificial neural network
title_sort tracking the chaotic behaviour of fractional-order chua’s system by mexican hat wavelet-based artificial neural network
publisher SAGE Publishing
series Journal of Low Frequency Noise, Vibration and Active Control
issn 1461-3484
2048-4046
publishDate 2019-12-01
description In this paper, a process is devised systematically to scrutinize the scrolling chaotic behaviour of fractional-order Chua's system. The process is composed of fractional Laplace transformation, artificial neural network with Mexican hat wavelet as an activation function and simulated annealing. Sequentially, the parametric expansion of fractional Laplace transform is employed to convert the governing fractional system into an ordinary differential system. Next, artificial neural network and simulated annealing approximate and optimize the attained system and produce accurate solutions. The predictability and elaboration of double scrolling chaotic structures of fractional-order Chua's system are also studied using the Lyapunov exponent and fifth–fourth Runge–Kutta method. Moreover, the mean absolute error and root mean square error are measured for the convergence analysis of the proposed scheme. On the whole, the accurate approximate solutions, the phase plots of Lyapunov exponent spectrum and bifurcation maps of the dynamical evolution of fractional Chua's system are a triumph of this endeavour.
url https://doi.org/10.1177/1461348418813015
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