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优化高精度混沌系统的 FPGA 实现以提高性能。

Optimizing FPGA implementation of high-precision chaotic systems for improved performance.

机构信息

Department of Engineering, Cardiff School of Technologies, Cardiff Metropolitan University, Cardiff, United Kingdom.

Department of Electrical Engineering, Faculty of Engineering, German International University, Cairo, Egypt.

出版信息

PLoS One. 2024 Apr 9;19(4):e0299021. doi: 10.1371/journal.pone.0299021. eCollection 2024.

DOI:10.1371/journal.pone.0299021
PMID:38593148
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11003634/
Abstract

Developing chaotic systems-on-a-chip is gaining much attention due to its great potential in securing communication, encrypting data, generating random numbers, and more. The digital implementation of chaotic systems strives to achieve high performance in terms of time, speed, complexity, and precision. In this paper, the focus is on developing high-speed Field Programmable Gate Array (FPGA) cores for chaotic systems, exemplified by the Lorenz system. The developed cores correspond to numerical integration techniques that can extend to the equations of the sixth order and at high precision. The investigation comprises a thorough analysis and evaluation of the developed cores according to the algorithm complexity and the achieved precision, hardware area, throughput, power consumption, and maximum operational frequency. Validations are done through simulations and careful comparisons with outstanding closely related work from the recent literature. The results affirm the successful creation of highly efficient sixth-order Lorenz discretizations, achieving a high throughput of 3.39 Gbps with a precision of 16 bits. Additionally, an outstanding throughput of 21.17 Gbps was achieved for the first-order implementation coupled with a high precision of 64 bits. These outcomes set our work as a benchmark for high-performance characteristics, surpassing similar investigations reported in the literature.

摘要

由于在保障通信安全、数据加密、随机数生成等方面具有巨大潜力,混沌系统芯片的开发受到了广泛关注。混沌系统的数字实现旨在在时间、速度、复杂性和精度方面实现高性能。本文专注于开发高速现场可编程门阵列(FPGA)混沌系统核,以 Lorenz 系统为例。所开发的核对应于数值积分技术,可以扩展到六阶方程,并具有高精度。根据算法复杂度和实现精度、硬件面积、吞吐量、功耗和最高工作频率,对所开发的核进行了全面分析和评估。通过仿真和与近期文献中优秀的密切相关工作的仔细比较进行了验证。结果证实了高效的六阶 Lorenz 离散化的成功创建,实现了 16 位精度下 3.39 Gbps 的高吞吐量。此外,还实现了 21.17 Gbps 的出色吞吐量,用于与高精度 64 位相结合的一阶实现。这些结果使我们的工作成为高性能特征的基准,超过了文献中报道的类似研究。

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本文引用的文献

1
Design of fast state observers using a backstepping-like approach with application to synchronization of chaotic systems.基于类反步法的快速状态观测器设计及其在混沌系统同步中的应用
Chaos. 2008 Jun;18(2):023114. doi: 10.1063/1.2907737.
2
Parameter identification technique for uncertain chaotic systems using state feedback and steady-state analysis.
Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Mar;77(3 Pt 2):036212. doi: 10.1103/PhysRevE.77.036212. Epub 2008 Mar 19.
3
A nonlinear controller design for permanent magnet motors using a synchronization-based technique inspired from the Lorenz system.一种基于受洛伦兹系统启发的同步技术的永磁电机非线性控制器设计。
Chaos. 2008 Mar;18(1):013111. doi: 10.1063/1.2840779.