White Noise Analysis and Chaos Expansions

Abstract:

In the framework of white noise analysis, random variables and stochastic processes can be represented in terms of Fourier series in a Hilbert space orthogonal basis, namely in their chaos expansion forms. We briefly summarize basic concepts and notations of white noise analysis, characterize different classes of stochastic processes (test, square integrable and generalized stochastic processes) in terms of their chaos expansion representations and review the main properties of the Wick calculus and stochastic integration.

Año de publicación:

2017

Keywords:

Fuente:

scopus