A New Memristive System with Chaotic and Periodic Bursting and Its FPGA Implementation

Wan, Qiuzhen; Li, Fēi; Liu, Jiong; Chen, Simiao; Yan, Zidie

doi:10.1007/s00034-022-02136-x

Cited by 6 publications

(1 citation statement)

References 15 publications

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“…In recent years, researchers have been employing memristors to simulate the effects of electromagnetic radiation and induced currents on neural networks. This approach facilitates the study of the interaction between electromagnetic radiation and neural systems, opening avenues for investigating the impact of radiation on neurological processes and developing novel therapeutic interventions [26][27][28], especially on learning and memory ability. Lin et al investigated the influence of electromagnetic radiation on the chaotic dynamics of a neural network [29].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Analysis and FPGA Implementation of a New Fractional-Order Hopfield Neural Network System under Electromagnetic Radiation

Yu,

Lin,

et al. 2023

Biomimetics

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Fractional calculus research indicates that, within the field of neural networks, fractional-order systems more accurately simulate the temporal memory effects present in the human brain. Therefore, it is worthwhile to conduct an in-depth investigation into the complex dynamics of fractional-order neural networks compared to integer-order models. In this paper, we propose a magnetically controlled, memristor-based, fractional-order chaotic system under electromagnetic radiation, utilizing the Hopfield neural network (HNN) model with four neurons as the foundation. The proposed system is solved by using the Adomain decomposition method (ADM). Then, through dynamic simulations of the internal parameters of the system, rich dynamic behaviors are found, such as chaos, quasiperiodicity, direction-controllable multi-scroll, and the emergence of analogous symmetric dynamic behaviors in the system as the radiation parameters are altered, with the order remaining constant. Finally, we implement the proposed new fractional-order HNN system on a field-programmable gate array (FPGA). The experimental results show the feasibility of the theoretical analysis.

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