A Fast DFA Algorithm for Multifractal Multiscale Analysis of Physiological Time Series.

ABSTRACT: Detrended fluctuation analysis (DFA) is a popular tool in physiological and medical studies for estimating the self-similarity coefficient, α, of time series. Recent researches extended its use for evaluating multifractality (where α is a function of the multifractal parameter q) at different scales n. In this way, the multifractal-multiscale DFA provides a bidimensional surface α(q,n) to quantify the level of multifractality at each scale separately. We recently showed that scale resolution and estimation variability of α(q,n) can be improved at each scale n by splitting the series into maximally overlapped blocks. This, however, increases the computational load making DFA estimations unfeasible in most applications. Our aim is to provide a DFA algorithm sufficiently fast to evaluate the

SUBMITTER: Castiglioni P 

PROVIDER: S-EPMC6405643 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature