Dynamic Analysis and Audio Encryption Application in IoT of a Multi-Scroll Fractional-Order Memristive Hopfield Neural Network

Fractional-order chaotic systems are widely used in the field of encryption because of its initial value sensitivity and historical memory. In this paper, the fractional-order definition of Caputo is introduced based on a nonideal flux-controlled memristive Hopfield neural network model, when changi...

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Bibliographic Details
Published inFractal and fractional Vol. 6; no. 7; p. 370
Main Authors Yu, Fei, Yu, Qiulin, Chen, Huifeng, Kong, Xinxin, Mokbel, Abdulmajeed Abdullah Mohammed, Cai, Shuo, Du, Sichun
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.07.2022
Subjects
audio encryption
Behavior
Brain research
Chaos theory
Decomposition
Eigenvalues
Equilibrium
Fault diagnosis
fractional-order
Information processing
Internet of Things
Mathematical models
memristive hopfield neural network (MHNN)
MQTT for IoT
Neural networks
Neurons
Queueing
Raspberry Pi
Telemetry
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Summary:Fractional-order chaotic systems are widely used in the field of encryption because of its initial value sensitivity and historical memory. In this paper, the fractional-order definition of Caputo is introduced based on a nonideal flux-controlled memristive Hopfield neural network model, when changing the parameters of the fractional-order memristive Hopfield neural network (FMHNN) can generate a different amount of multi-scroll attractors. Some dynamical behaviors are investigated by numerical simulation, especially analyzed coexistence and bifurcation under different orders and different coupling strengths. The results show that the chaotic system of FMHNN has abundant dynamic behaviors. In addition, a chaotic audio encryption scheme under a Message Queueing Telemetry Transport (MQTT) protocol is proposed and implemented by Raspberry Pi; the audio encryption system based on FMHNN has a broad future in intelligent home and other IoT applications.
ISSN:2504-3110
2504-3110
DOI:10.3390/fractalfract6070370