APPROXIMATE SOLUTION ALGORITHMS FOR NONLINEAR FILTER PROBLEMS,

Abstract

This paper presents a summary and evaluation of several approximation procedures which may be used to obtain maximum a-posterior density estimates, least integral square error and minimum covariance of error sequential state and parameter estimators in nonlinear systems. A simple example which illustrates the similarities and differences of the computational algorithms for the various methods is presented. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1968
Accession Number
AD0676802

Entities

People

  • Andrew P. Sage
  • William S. Ewing

Organizations

  • Southern Methodist University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Covariance
  • Data Science
  • Estimators
  • Information Science
  • Integrals
  • Mathematics
  • Nonlinear Systems
  • Statistical Algorithms
  • Statistical Analysis
  • Test And Evaluation

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.