The Measurability of a Stochastic Process of Second Order and Its Linear Space,

Abstract

It is of considerable theoretical and practical interest to know whether a stochastic process has a measurable modification. For the important clan of second order processes, simple necessary and sufficient conditions for the existence of a measurable modification are given in terms of the autocorrelation function of the process. These conditions are the measurability of the autocorrelation of the process and the separability of its reproducing kernel Hilbert space or its linear space. It is shown that weakly continuous processes, processes with orthogonal increments and second order martingales have always measurable modifications. Also necessary and sufficient conditions are given in terms of integral representations, for the linear space of a second order process to be separable. As a consequence it is shown that a second order process is oscillatory if and only if its linear space is separable. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1972
Accession Number
AD0751288

Entities

People

  • Stamatis Cambanis

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Autocorrelation
  • Data Science
  • Hilbert Space
  • Information Science
  • Integrals
  • Mathematical Analysis
  • Mathematics
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Mathematical Modeling and Probability Theory.

Technology Areas

  • Space