A Novel Exact Representation of Stationary Colored Gaussian Processes (Fractional Differential Approach)

Abstract

A novel representation of functions, called generalized Taylor form, is applied to the filtering of white noise processes. It is shown that every Gaussian colored noise can be expressed as the output of a set of linear fractional stochastic differential equation whose solution is a weighted sum of fractional Brownian motions. The exact form of the weighting coefficients is given and it is shown that it is related to the fractional moments of the target spectral density of the colored noise.

References in corpus (2)

• Fractional calculus approach to the statistical characterization of random variables and vectors
• On the use of fractional calculus for the probabilistic characterization of random variables

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