From phase space to frequency domain: a time-frequency analysis for chaotic time series

Abstract

Time-frequency analysis is performed for chaotic flow with a power spectrum estimator based on the phase-space neighborhood. The relation between the reference phase point and its nearest neighbors is demonstrated. The nearest neighbors, representing the state recurrences in the phase space reconstructed by time delay embedding, actually cover data segments with similar wave forms and thus possess redundant information, but recur with no obvious temporal regularity. To utilize this redundant recurrence information, a neighborhood-based spectrum estimator is devised. Then time-frequency analysis with this estimator is performed for the Lorenz time series, the Rössler time series, experimental laser data, and colored noise. Features revealed by the spectrogram can be used to distinguish noisy chaotic flow from colored noise.