Brownian motion but rather a singular behavior in which the particle doesn't move at all. The Brownian motion can be modeled by a random walk. Random walks in porous media or fractals are anomalous. In the general case, Brownian motion is a non-Markov random process and described by stochastic integral equations. The French mathematician Paul Lévy proved the following theorem, which gives a necessary and sufficient condition for a continuous R-valued stochastic process "X" to actually be "n"-dimensional Brownian motion. Hence, Lévy's condition can actually be used as an alternative definition of Brownian motion. Let "X" = ("X", ..., "X") be a
Fractional Brownian motion Friedrich Gauss. Prior to the introduction of the fractional Brownian motion, used the Riemann–Liouville fractional integral to define the process where integration is with respect to the white noise measure "dB"("s"). This integral turns out to be ill-suited to applications of fractional Brownian motion because of its over-emphasis of the origin . The idea instead is to use a different fractional integral of white noise to define the process: the Weyl integral for "t" > 0 (and similarly for "t" < 0). The main difference between fractional Brownian motion and regular Brownian motion is that while the increments in Brownian