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Dynamic Analysis and FPGA Implementation of a New Fractional-Order Hopfield Neural Network System under Electromagnetic Radiation.
Yu, Fei; Lin, Yue; Xu, Si; Yao, Wei; Gracia, Yumba Musoya; Cai, Shuo.
Afiliação
  • Yu F; School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 410114, China.
  • Lin Y; School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 410114, China.
  • Xu S; School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 410114, China.
  • Yao W; School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 410114, China.
  • Gracia YM; School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 410114, China.
  • Cai S; School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 410114, China.
Biomimetics (Basel) ; 8(8)2023 Nov 21.
Article em En | MEDLINE | ID: mdl-38132498
ABSTRACT
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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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article