Hurst exponent

The Hurst exponent is used as a measure of long-term memory of time series. It relates to the autocorrelations of the time series, and the rate at which these decrease as the lag between pairs of values increases. Studies involving the Hurst exponent were originally developed in hydrology for the practical matter of determining optimum dam sizing for the Nile river's volatile rain and drought conditions that had been observed over a long period of time. The name "Hurst exponent", or "Hurst coefficient", derives from Harold Edwin Hurst (1880–1978), who was the lead researcher in these studies; the use of the standard notation H for the coefficient also relates to his name. In fractal geometry, the generalized Hurst exponent has been denoted by H or Hq in honor of both Harold Edwin Hurst and Ludwig Otto Hölder (1859–1937) by Benoît Mandelbrot (1924–2010). H is directly related to fractal dimension, D, and is a measure of a data series' "mild" or "wild" randomness. The Hurst exponent i

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Both natural and manufactured surfaces have been found to be self-affine over many length scales. Yet, it is still not understood what mechanisms lead to the final self-affine morphology, which is characterized by a persistent Hurst exponent (greater than 0.5, see next section 2.1 for the definitions). The scope of this project is then to develop new discrete growth models that can help gather insights in the formation of self-affine surfaces in frictional processes.

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