STATISTICAL-PROBABLE MODELING OF RANDOM PROCESSES

Abstract

Operational and tactical calculations, as well as scientific and technical investigations, often involve consideration of random phenomena and processes which can be characterized by statistical parameters calculated as averages of observed (selected) values. The statistical probability modeling method for random processes suggested used the Monte Carlo method as its mathematical base, and the article proceeds to describe its application to two practical examples, one of which is the calculation of the process involved in a missile closing a target; the other reproducing an actual noise process in accordance with the normal distribution law. The mathematical method described involves the use of an electronic computer to obtain the statistical evaluation of characteristics with required accuracy and to reproduce the probability models of the subjects under investigation using experimental data based on distribution laws and correlated ties in the elements of those subjects, without waiting for the development of an analytical theory and the disclosure of the physical content of those subjects.

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Document Details

Document Type
Technical Report
Publication Date
Jul 11, 1968
Accession Number
AD0682169

Entities

People

  • A. S. Zhernenko

Organizations

  • National Air and Space Intelligence Center

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Coefficients
  • Computers
  • Data Science
  • Digital Computers
  • Distribution Functions
  • Experimental Data
  • Foreign Technology
  • Information Science
  • Integrals
  • Monte Carlo Method
  • Normal Distribution
  • Probability
  • Probability Distributions
  • Rocket Targets
  • Stationary Processes
  • Targets

Readers

  • Computational Modeling and Simulation
  • Statistical inference.
  • Systems Analysis and Design

Technology Areas

  • Microelectronics