Bandt Christoph, Pompe Bernd
Institute of Mathematics and Institute of Physics, University of Greifswald, Greifswald, Germany.
Phys Rev Lett. 2002 Apr 29;88(17):174102. doi: 10.1103/PhysRevLett.88.174102. Epub 2002 Apr 11.
We introduce complexity parameters for time series based on comparison of neighboring values. The definition directly applies to arbitrary real-world data. For some well-known chaotic dynamical systems it is shown that our complexity behaves similar to Lyapunov exponents, and is particularly useful in the presence of dynamical or observational noise. The advantages of our method are its simplicity, extremely fast calculation, robustness, and invariance with respect to nonlinear monotonous transformations.
我们基于相邻值的比较为时间序列引入复杂性参数。该定义直接适用于任意现实世界的数据。对于一些著名的混沌动力系统，结果表明我们的复杂性与李雅普诺夫指数表现相似，并且在存在动态或观测噪声的情况下特别有用。我们方法的优点在于其简单性、计算速度极快、稳健性以及对非线性单调变换的不变性。
