ABSTRACT WIENER PROCESSES AND THEIR REPRODUCING KERNEL HILBERT SPACES.

Abstract

The paper explores the relationship between Gaussian processes and their associated RKH Spaces. A simple proof of Gross's theorem on abstract Wiener spaces is given. For a Gaussian measure mu with continuous covariance R defined on the Banach space C(T) of real continuous functions on T (T being a separable complete metric space) it is shown that the closure of H(R) in C(T) is the support of mu. This result is extended to Gaussian measures on arbitrary separable Banach spaces. A necessary and sufficient criterion for a separable Gaussian process x(t) (0 = or < t = or < 1) with continuous covariance R to have continuous sample paths is furnished by the following result to the effect that the canonical normal distribution on H(R) extends to a Gaussian measure on C(0,1) if and only if the sup-norm on H(R) is measurable in the sense of Gross. (Author)

Document Details

Document Type
Technical Report
Publication Date
Aug 08, 1969
Accession Number
AD0695688

Entities

People

  • G. Kallianpur

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Banach Space
  • Covariance
  • Data Science
  • Distribution Functions
  • Functions (Mathematics)
  • Gaussian Processes
  • Hilbert Space
  • Information Science
  • Mathematical Analysis
  • Mathematics
  • Normal Distribution
  • Statistical Functions

Fields of Study

  • Mathematics

Readers

  • Mathematical Modeling and Probability Theory.
  • Mathematics or Statistics

Technology Areas

  • Space