Some Probabilistic and Empirical Aspects of Chebyshev Estimation and Identification,

Abstract

Because the actual shape of a model's response may be more important than the value of an index such as the integral squared error, a probabilistic and empirical study has been made of parameter and state estimates that minimize the maximum error between plant and model outputs. Preliminary results indicate that minimax estimation compares favorably with estimations based upon a minimum squared error criterion. It is further shown that if the measurement noise is characterized by a distribution function which is continuous, symmetric and differentiable, then the estimate of the measurement will be unbiased. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1972
Accession Number
AD0739601

Entities

People

  • Howard Kaufman
  • Michael S. Howard

Organizations

  • Rensselaer Polytechnic Institute

Tags

DTIC Thesaurus Topics

  • Distribution Functions
  • Identification
  • Integrals
  • Measurement

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Approximation Theory.