Methodology for Stochastic Modeling.

Abstract

The requirement to develop stochastic mathematical models arises across the whole range of engineering and applied research where observations are made of a physical process, corrupted by noise, and it is desired to determine the underlying nature, either in time or frequency, of the observed phenomenon. This paper presents some of the current approaches in stochastic modeling, including adaptive autoregressive models, which have been found to be useful in this area. Additional keywords: Covariance; Moving average; Box Jenkins method. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1985
Accession Number
ADA158851

Entities

People

  • H. E. Cohen

Organizations

  • United States Army Materiel Systems Analysis Activity

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Army
  • Autocorrelation
  • Coefficients
  • Covariance
  • Eigenvalues
  • Engineering
  • Equations
  • Frequency
  • Mathematical Models
  • Models
  • Noise
  • Observation
  • Signal Processing
  • Systems Analysis
  • White Noise

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Modeling and Simulation