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Measures of signal complexity, such as the Hurst exponent, the fractal dimension, and the Spectrum of Lyapunov exponents, are used in time series analysis to give estimates on persistency, anti-persistency, fluctuations and predictability of the data under study. They have proven beneficial when doing time series prediction using machine and deep learning and tell what features may be relevant for predicting time-series and establishing complexity features. Further, the performance of machinedoi:10.3390/e23121672 pmid:34945978 pmcid:PMC8700684 fatcat:ppvnllvlhvemtpxkitg4aapvxe