Siddagangaiah Shashidhar, Li Yaan, Guo Xijing, Yang Kunde
School of Marine Science and Technology, Northwestern Polytechnical University, Xian 710072, China.
Chaos. 2015 Oct;25(10):103117. doi: 10.1063/1.4932561.
Two decades ago, it was shown that ambient noise exhibits low dimensional chaotic behavior. Recent new techniques in nonlinear science can effectively detect the underlying dynamics in noisy time series. In this paper, the presence of low dimensional deterministic dynamics in ambient noise is investigated using diverse nonlinear techniques, including correlation dimension, Lyapunov exponent, nonlinear prediction, and entropy based methods. The consistent interpretation of different methods demonstrates that ambient noise can be best modeled as nonlinear stochastic dynamics, thus rejecting the hypothesis of low dimensional chaotic behavior. The ambient noise data utilized in this study are of duration 60 s measured at South China Sea.
二十年前,研究表明环境噪声呈现低维混沌行为。非线性科学中的最新技术能够有效检测有噪声时间序列中的潜在动力学。本文运用多种非线性技术,包括关联维数、李雅普诺夫指数、非线性预测以及基于熵的方法,研究环境噪声中低维确定性动力学的存在情况。不同方法的一致解释表明,环境噪声最好被建模为非线性随机动力学,从而否定了低维混沌行为的假设。本研究中使用的环境噪声数据时长为60秒,是在南海测量得到的。