Accession Number:

AD0758756

Title:

Test Input Evaluation for Optimal Adaptive Filtering.

Descriptive Note:

Rept. for Jun-Oct 72,

Corporate Author:

AEROSPACE CORP EL SEGUNDO CALIF ENGINEERING SCIENCE OPERATIONS

Personal Author(s):

• Smith,Patrick L.

Report Date:

1972-11-07

Pagination or Media Count:

14.0

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

Descriptors:

• (*ADAPTIVE CONTROL SYSTEMS
• MATHEMATICAL MODELS)
• INFORMATION THEORY
• IDENTIFICATION SYSTEMS
• TRANSFER FUNCTIONS
• STOCHASTIC PROCESSES
• OPTIMIZATION

Subject Categories:

• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE