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原文連結
論文資訊
- 類型：已發表論文
- 日期：2015-04-13
摘要
In 1980 and 1981, two pioneering papers laid the foundation for what became known as 非線性 time-series analysis: the analysis of observed data-typically univariate-via dynamical systems theory. Based on the concept of state-space reconstruction, this set of methods allows us to compute characteristic quantities such as 李雅普諾夫 exponents and 碎形 dimensions, to predict the future course of the time series, and even to reconstruct the equations of motion in some cases. In practice, however, there are a number of issues that restrict the power of this approach: whether the signal accurately and thoroughly samples the dynamics, for instance, and whether it contains noise. Moreover, the numerical algorithms that we use to instantiate these ideas are not perfect; they involve approximations, scale par
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