Brownian noise a white noise signal: meaning that Brownian motion is the integral of the white noise formula_2, whose power spectral density is flat: Note that here formula_4 denotes the Fourier transform, and formula_5 is a constant. An important property of this transform is that the derivative of any distribution transforms as from which we can conclude that the power spectrum of Brownian noise is Brown noise can be produced by integrating white noise. That is, whereas (digital) white noise can be produced by randomly choosing each sample independently, Brown noise can be produced by adding a random offset to each sample
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