A simple and fast representation space for classifying complex time series

作者：Zunino Luciano^*; Olivares Felipe; Bariviera Aurelio F; Rosso Osvaldo A

来源：Physics Letters, Section A: General, Atomic and Solid State Physics , 2017, 381(11): 1021-1028.

DOI：10.1016/j.physleta.2017.01.047

• Time series analysis
• Abbe value
• Turning points
• Financial data
• Electroencephalogram data
• Heart rate variability

In the context of time series analysis considerable effort has been directed towards the implementation of efficient discriminating statistical quantifiers. Very recently, a simple and fast representation space has been introduced, namely the number of turning points versus the Abbe value. It is able to separate time series from stationary and non-stationary processes with long-range dependences. In this work we show that this bidimensional approach is useful for distinguishing complex time series: different sets of financial and physiological data are efficiently discriminated. Additionally, a multiscale generalization that takes into account the multiple time scales often involved in complex systems has been also proposed. This multiscale analysis is essential to reach a higher discriminative power between physiological time series in health and disease.

• 出版日期2017-3-18