论文标题
顺序光谱：复杂时间序列的频域表征
Ordinal spectrum: a frequency domain characterization of complex time series
论文作者
论文摘要
尽管经典光谱分析是表征线性系统的自然方法，但它无法描述混乱的动力学。在这里，我们提出了基于符号序列的光谱转换的方法，以表征时间序列的复杂性。与其他非线性映射函数（例如状态空间重建）相反，提出的表示是一种自然的方法，可以在频域中区分混乱的行为。我们在不同的合成和现实世界数据中测试该方法。我们的结果表明，所提出的方法可以为在不同的实际数据中观察到的非线性振荡提供新的见解。
Although classical spectral analysis is a natural approach to characterise linear systems, it cannot describe a chaotic dynamics. Here, we propose the ordinal spectrum, a method based on a spectral transformation of symbolic sequences, to characterise the complexity of a time series. In contrasts with other nonlinear mapping functions (e.g. the state-space reconstruction) the proposed representation is a natural approach to distinguish, in a frequency domain, a chaotic behavior. We test the method in different synthetic and real-world data. Our results suggest that the proposed approach may provide new insights into the non-linear oscillations observed in different real data.
