Fractal analysis
Mathematical technique in data science / From Wikipedia, the free encyclopedia
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Fractal analysis is assessing fractal characteristics of data. It consists of several methods to assign a fractal dimension and other fractal characteristics to a dataset which may be a theoretical dataset, or a pattern or signal extracted from phenomena including topography,[1] natural geometric objects, ecology and aquatic sciences,[2] sound, market fluctuations,[3][4][5] heart rates,[6] frequency domain in electroencephalography signals,[7][8] digital images,[9] molecular motion, and data science. Fractal analysis is now widely used in all areas of science.[10] An important limitation of fractal analysis is that arriving at an empirically determined fractal dimension does not necessarily prove that a pattern is fractal; rather, other essential characteristics have to be considered.[11] Fractal analysis is valuable in expanding our knowledge of the structure and function of various systems, and as a potential tool to mathematically assess novel areas of study. Fractal calculus was formulated which is a generalization of ordinary calculus. [12]