System Identification Using Bayesian Estimation.

Abstract

The problem of identifying a system with a known structure and input is formulated as a nonlinear estimation problem. The problem is solved using equations derived from Bayes' method. The computational burden usually associated with this method is reduced by approximating the conditional density function with Hermite polynomials. A numerical example demonstrates the effectiveness of the proposed technique. (Author)

Document Details

Document Type
Technical Report
Publication Date
Oct 15, 1973
Accession Number
AD0771768

Entities

People

  • Calvin Hecht

Organizations

  • The Aerospace Corporation

Tags

DTIC Thesaurus Topics

  • Equations
  • Identification
  • Polynomials

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Life Cycle Cost Analysis
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms