https://doi.org/10.1140/epjs/s11734-024-01173-8
Regular Article
Dynamic research of hidden attractors in discrete memristive neural network with trigonometric functions and FPGA implementation
1
School of Computer and Communication Engineering, Changsha University of Science and Technology, 410076, Changsha, China
2
Hunan Post and Telecommunication Planning and Designing Institute, No. 236 Yuanda Road, 410126, Changsha, China
Received:
6
November
2023
Accepted:
12
April
2024
Published online:
22
April
2024
Compared with the traditional chaotic discrete neural network model with monotonic input–output function, the discrete neural network model with trigonometric function has greater memory capacity and embedded mode recovery ability. It is precisely because of the non-monotonic characteristics of periodic functions that neurons with trigonometric functions show rich chaotic dynamic behaviors at the same time. In this paper, we introduce an exponential function and a quadratic term to construct a discrete memristor. The constructed discrete memristor is introduced into a discrete neural network with trigonometric function. Through research and analysis, we find that there is no equilibrium point in the discrete memristive neural network, that is, the chaotic attractor generated by the system is a hidden attractor. In addition, Lyapunov exponential spectrum and bifurcation diagram analysis show that the system has rich dynamic behaviors such as the coexistence of attractors. Finally, we carried out a hardware experiment based on FPGA. The experimental results are consistent with the MATLAB simulation results, which verifies the feasibility of the system.
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© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.