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 : 07 NOV 1972
Pagination or Media Count : 14
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