Identification of Dynamical Systems in the Presence of Non-Gaussian and Non-Whie Noise.

Abstract

Analysis of test results indicates that the measurement and process noise is significantly non-white and non-Gaussian. Some analyses indicate that 10% to 15% of the data points may deviate significantly from non-Gaussian distribution. In addition, numerous sources lead to non-white noise. These errors effect both the accuracy of state and parameter estimates as well as the estimation of accuracy levels. In this report, techniques have been developed to treat systems with non-white and non-Gaussian noise. These techniques provide good estimates under given whiteness and Gaussianess conditions. The procedures are simple and can be easily incorporated in the standard maximum likelihood and model structure determination methods.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1979
Accession Number
ADA083645

Entities

People

  • H. Salzwedel
  • Naman Gupta
  • W. E. Hall

Tags

Communities of Interest

  • Biomedical
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Data Science
  • Distribution Functions
  • Estimators
  • Gaussian Distributions
  • Information Processing
  • Information Science
  • Information Theory
  • Kalman Filters
  • Mathematical Filters
  • Optimal Estimators
  • Probability Density Functions
  • Probability Distributions
  • Random Variables
  • Statistical Algorithms
  • Statistical Analysis
  • Stochastic Processes
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Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.