Failure in distinguishing colored noise from chaos using the "noise titration" technique
Failure in distinguishing colored noise from chaos using the "noise titration" technique
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DOI：
10.1103/physreve.79.035201
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发表时间：
2009-03-01
影响因子：
2.4
通讯作者：
Aguirre, Luis A.
中科院分区：
文献类型：
--
作者：
Freitas, Ubiratan S.;Letellier, Christophe;Aguirre, Luis A.
识别实验数据中的混沌——噪声数据——仍然是一个具有挑战性的问题，因此很难提供结论性的论据。为了避免基于几何不变量（维度，李雅普诺夫指数等）的技术通常遇到的问题，Poon和Barahona引入了一种数值滴定程序，该程序比较了线性和非线性模型的一步预测[Proc. Natl]。学会科学。美国法典98,7107(2001)]。我们在有色噪声或其他类型的非混沌行为的背景下研究上述技术。主要的结论是，在几个例子中，噪声滴定法无法将这种非混沌信号与低维确定性混沌区分开来。
Identifying chaos in experimental data-noisy data-remains a challenging problem for which conclusive arguments are still very difficult to provide. In order to avoid problems usually encountered with techniques based on geometrical invariants (dimensions, Lyapunov exponent, etc.), Poon and Barahona introduced a numerical titration procedure which compares one-step-ahead predictions of linear and nonlinear models [Proc. Natl. Acad. Sci. U.S.A. 98, 7107 (2001)]. We investigate the aformentioned technique in the context of colored noise or other types of nonchaotic behaviors. The main conclusion is that in several examples noise titration fails to distinguish such nonchaotic signals from low-dimensional deterministic chaos.