Fractional Brownian Vector Fields
This work puts forward an extended definition of vector fractional Brownian motion (fBm) using a distribution theoretic formulation in the spirit of Gel′fand and Vilenkin's stochastic analysis. We introduce random vector fields that share the statistical invariances of standard vector fBm (self-similarity and rotation invariance) but which, in contrast, have dependent vector components in the general case. These random vector fields result from the transformation of white noise by a special operator whose invariance properties the random field inherits. The said operator combines an inverse fractional Laplacian with a Helmholtz-like decomposition and weighted recombination. Classical fBm's can be obtained by balancing the weights of the Helmholtz components. The introduced random fields exhibit several important properties that are discussed in this paper. In addition, the proposed scheme yields a natural extension of the definition to Hurst exponents greater than one.
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Keywords: fractional Brownian motion ; random vector fields ; self-similarity ; invariance ; Helmholtz decomposition ; generalized random processes ; Gel'fand-Vilenkin stochastic analysis ; Fractal Processes ; Self-Similarity ; Wavelets ; Motion ; Representation ; Decomposition ; Divergence ; Turbulence ; Splines ; Models
Record created on 2011-02-17, modified on 2016-08-09