Multifractal system

A multifractal system is a generalization of a fractal system in which a single exponent (the fractal dimension) is not enough to describe its dynamics; instead, a continuous spectrum of exponents (the so-called singularity spectrum) is needed.^[1]

Multifractal systems are common in nature. They include the length of coastlines, mountain topography,^[2] fully developed turbulence, real-world scenes, heartbeat dynamics,^[3] human gait^[4] and activity,^[5] human brain activity,^{[6][7][8][9][10][11][12]} and natural luminosity time series.^[13] Models have been proposed in various contexts ranging from turbulence in fluid dynamics to internet traffic, finance, image modeling, texture synthesis, meteorology, geophysics and more.^{[citation needed]} The origin of multifractality in sequential (time series) data has been attributed to mathematical convergence effects related to the central limit theorem that have as foci of convergence the family of statistical distributions known as the Tweedie exponential dispersion models,^[14] as well as the geometric Tweedie models.^[15] The first convergence effect yields monofractal sequences, and the second convergence effect is responsible for variation in the fractal dimension of the monofractal sequences.^[16]

Multifractal analysis is used to investigate datasets, often in conjunction with other methods of fractal and lacunarity analysis. The technique entails distorting datasets extracted from patterns to generate multifractal spectra that illustrate how scaling varies over the dataset. Multifractal analysis has been used to decipher the generating rules and functionalities of complex networks.^[17] Multifractal analysis techniques have been applied in a variety of practical situations, such as predicting earthquakes and interpreting medical images.^[18][19][20]