Accession Number:

ADD019242

Title:

Model Identification and Characterization of Error Structures in Signal Processing.

Descriptive Note:

Patent filed 13 Jan 97,patented 21 Jul 98

Corporate Author:

OFFICE OF THE SECRETARY OF THE NAVY WASHINGTON DC

Report Date:

1998-07-21

Pagination or Media Count:

7.0

Abstract:

A METHOD FOR FINDING A PROBABILITY DENSITY FUNCTIONPDF AND ITS STATISTICAL MOMENTS FOR AN ARBITRARY EXPONENTIAL FUNCTION OF THE FORM GXALPHAXME-BETAXN, 0XINFINITY WHERE ALPHA, BETA, N 0, M -1 ARE REAL CONSTANTS IN ONE DIMENSIONAL DISTRIBUTIONS AND GX SUB 1,X SUB 2,...,X SUB 1 IN THE HYPERPLANE. NON-LINEAR REGRESSION ANALYSES ARE PERFORMED ON THE DATA DISTRIBUTION AND A ROOT-MEAN-SQUARE RMS IS CALCULATED AND RECORDED FOR EACH SOLUTION SET UNTIL CONVERGENCE. THE BASIS FUNCTION IS RECONSTRUCTED FROM THE ESTIMATES IN THE FINAL SOLUTION SET AND A PDF IS OBTAINED. THE MOMENT GENERATING FUNCTION MGF, WHICH CHARACTERIZES ANY STATISTICAL MOMENT OF THE DISTRIBUTION, IS OBTAINED USING A NOVEL FUNCTION DERIVED BY THE INVENTORS AND THE MEAN AND VARIANCE ARE OBTAINED IN STANDARD FASHION. SIMPLE HYPOTHESES ABOUT THE BEHAVIOR OF SUCH FUNCTIONAL FORMS MAY BE TESTED STATISTICALLY ONCE THE EMPIRICAL LEAST SQUARES METHODS HAVE IDENTIFIED AN APPLICABLE MODEL DERIVED FROM ACTUAL MEASUREMENTS.

Subject Categories:

  • Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE