Two-Dimensional Coupled Complex Chaotic Map

IF 9.9 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Industrial Informatics Pub Date : 2024-09-23 DOI:10.1109/TII.2024.3431085
Zhongyun Hua;Jinhui Yao;Yinxing Zhang;Han Bao;Shuang Yi
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Abstract

Chaotic systems have attracted extensive research due to their pseudorandomness, ergodicity, and unique properties. Most studies focus on chaotic systems in the real number domain, but recent research has explored the design of complex chaotic systems. However, the chaotic behaviors of previous complex chaotic systems can only be observed through experiments and lack theoretical proof. In this article, we construct a 2-D coupled complex chaotic (2D-CCC) map using two nonlinear functions in the complex number domain. We theoretically prove the robust and complex chaotic behavior of the 2D-CCC map using the Lyapunov exponent. In addition, we conduct extensive experiments to demonstrate the map's intricate dynamics and high performance indicators. Comparison results highlight its superiority over previous chaotic systems. We also implement our 2D-CCC map on a hardware platform to validate its implementation feasibility on hardware devices. Finally, we investigate the 2D-CCC map's application in pseudorandom number generation and the testing results validate the high degree of randomness in the generated pseudorandom numbers.
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二维耦合复杂混沌图
混沌系统由于其伪随机性、遍历性和独特的性质而引起了广泛的研究。大多数研究集中在实数域的混沌系统,但最近的研究已经探索了复杂混沌系统的设计。然而,以往复杂混沌系统的混沌行为只能通过实验来观察,缺乏理论证明。本文利用复数域上的两个非线性函数构造了二维耦合复混沌映射。利用李雅普诺夫指数从理论上证明了2D-CCC映射的鲁棒性和复杂混沌行为。此外,我们进行了大量的实验来证明地图的复杂动态和高性能指标。对比结果表明,该方法优于以往的混沌系统。我们还在硬件平台上实现了2D-CCC地图,以验证其在硬件设备上实现的可行性。最后,我们研究了2D-CCC地图在伪随机数生成中的应用,测试结果验证了生成的伪随机数具有很高的随机性。
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来源期刊
IEEE Transactions on Industrial Informatics
IEEE Transactions on Industrial Informatics 工程技术-工程:工业
CiteScore
24.10
自引率
8.90%
发文量
1202
审稿时长
5.1 months
期刊介绍: The IEEE Transactions on Industrial Informatics is a multidisciplinary journal dedicated to publishing technical papers that connect theory with practical applications of informatics in industrial settings. It focuses on the utilization of information in intelligent, distributed, and agile industrial automation and control systems. The scope includes topics such as knowledge-based and AI-enhanced automation, intelligent computer control systems, flexible and collaborative manufacturing, industrial informatics in software-defined vehicles and robotics, computer vision, industrial cyber-physical and industrial IoT systems, real-time and networked embedded systems, security in industrial processes, industrial communications, systems interoperability, and human-machine interaction.
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