Stochastic and Multiple Wiener Integrals for Gaussian Processes,

Abstract

Mulitple Wiener integrals and stochastic integrals are defined for Gaussian processes, extending the related notions for the Wiener process. It is shown that every L2-functional of a Gaussian process admits an adapted stochastic integral representation and an orthogonal series expansion in terms of multiple Wiener integrals. Also some results of Wiener's theory of nonlinear noise are generalized to noises other than white. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1976
Accession Number
ADA033249

Entities

People

  • Stamatis Cambanis
  • Steel T. Huang

Organizations

  • University of North Carolina at Chapel Hill

Tags

DTIC Thesaurus Topics

  • Air Force
  • Continuity
  • Covariance
  • Data Science
  • Gaussian Processes
  • Hilbert Space
  • Integrals
  • Noise
  • Path Integrals
  • Probability
  • Probability Distributions
  • Random Variables
  • Sequences
  • Stationary Processes
  • Step Functions
  • Stochastic Processes
  • White Noise

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Calculus or Mathematical Analysis