Test Input Evaluation for Optimal Adaptive Filtering.

Abstract

Average statistical divergence is proposed as a figure of merit for ranking test inputs used in identifying the unknown parameters of a system. Average divergence is a concept taken from communication theory; it can be computed a priori from a recursion relation derived in this paper. Two closed-form analytic examples are presented. The development in the paper is for linear multistage processes and is applicable to on-line nonstationary adaptive filtering problems. The average divergence of a general multistage process that has unknown parameters can be calculated recursively. (Author)

Document Details

Document Type
Technical Report
Publication Date
Nov 07, 1972
Accession Number
AD0758756

Entities

People

  • Patrick L. Smith

Organizations

  • The Aerospace Corporation

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Electrical Engineering
  • Engineering
  • Figure Of Merit
  • Filtration
  • Information Theory
  • Test And Evaluation

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Systems Analysis and Design