Skip to main content
SpringerLink
Log in

Estimate of the correlation function of a random process during measurements at random moments of time

  • Mathematical Processing of Physics Experimental Data
  • Published:
Russian Physics Journal Aims and scope

Abstract

Estimates are suggested for the correlation function of a stationary random process, when the measurement moments form a Poisson or recurrent sequence of events. The situation in which only the order of measurement moments is known is investigated.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Mathematical Reference Handbook: Tables of Integral Transformations [in Russian], Nauka, Moscow (1969), Vol. 1.

  2. M. A. Lavrent'ev and B. V. Shabat, Methods of Theory of Functions of a Complex Variable [in Russian], Nauka, Moscow (1973).

    Google Scholar 

  3. H. Cramer and M. R. Leadbetter, Stationary and Related Stochastic Processes, Wiley, New York (1967).

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Ship and Anchor Branch of the Tomsk Pedagogical Institute, Russia

    F. F. Idrisov

Authors
  1. F. F. Idrisov
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Fizika, No. 3, pp. 11–16, March. 1995.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Idrisov, F.F. Estimate of the correlation function of a random process during measurements at random moments of time. Russ Phys J 38, 225–230 (1995). https://doi.org/10.1007/BF00559464

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00559464

Keywords

Search

Navigation