由外部非对称双路滤波腔激光器辅助的加固型水库计算机

IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Chaos Solitons & Fractals Pub Date : 2024-10-12 DOI:10.1016/j.chaos.2024.115652
Deyu Cai , Penghua Mu , Yu Huang , Pei Zhou , Nianqiang Li
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引用次数: 0

摘要

混沌的特点是在确定性系统中出现不规则、类似随机的现象,被广泛应用于气象学、生命科学和物理学。精确的混沌预测对于极端天气预警和疾病预防至关重要。我们提出了一种光子时延存储计算(TDRC)系统,该系统在光注入下具有非对称双路径滤波光反馈,可用于混沌时间序列的短期预测。为了全面评估这种 TDRC 的短期预测性能,我们评估了两种不同的混沌时间序列(即 Santa-Fe 和 Mackey-Glass 混沌时间序列)以及内存容量。数值结果表明,拟议的 TDRC 在短期预测性能方面优于传统的双路光反馈系统。这归因于非对称双路径滤波光反馈增强了记忆容量。此外,我们还揭示了注入强度、反馈强度、滤波器带宽和虚拟节点数量对系统性能的影响。我们的工作为利用光子 TDRC 进行复杂混沌系统的短期精确预测提供了一条新途径。
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A reinforced reservoir computer aided by an external asymmetric dual-path-filtering cavity laser
Chaos, characterized by irregular, stochastic-like and occurring in deterministic systems, is widely used in meteorology, life sciences, and physics. Precise chaos predictions are crucial for early warning of extreme weather and disease prevention. We propose a photonic time-delay reservoir computing (TDRC) system with asymmetric dual-path filtering optical feedback under optical injection for short-term prediction of chaotic time series. To thoroughly evaluate the performance in short-term prediction provided by such TDRC, we assess two different chaotic time series, i.e., the Santa-Fe and Mackey-Glass chaotic time series, as well as the memory capacity. Numerical results indicate that the proposed TDRC outperforms the system with conventional dual-path optical feedback in short-term prediction performance. This is attributed to the enhanced memory capacity originating from the asymmetric dual-path filtering optical feedback. Additionally, we reveal the effects of the injection strength, feedback strength, filter bandwidth and the number of virtual nodes on the system performance. Our work provides a novel path for accurate short-term prediction of complex chaotic systems using photonic TDRC.
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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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