
Accession Number : AD0709228
Title : NONLINEAR FILTERING BY APPROXIMATION OF THE A POSTERIORI DENSITY,
Corporate Author : CALIFORNIA UNIV LOS ANGELES SCHOOL OF ENGINEERING AND APPLIED SCIENCE
Personal Author(s) : Sorenson,H. W. ; Stubberud,A. R.
Report Date : 1967
Pagination or Media Count : 31
Abstract : The problem of estimating from noisy measurement data the state of a dynamical system described by nonlinear difference equations is considered. The measurement data have a nonlinear relation with the state and are assumed to be available at discrete instants of time. A Bayesian approach to the problem is suggested in which the density function for the state conditioned upon the available measurement data is computed recursively. The evolution of the a posteriori density function cannot be described in a closed form for most systems; the class of linear systems with additive, white gaussian noise provides the major exception. Thus, the problem of nonlinear filtering can be viewed as essentially, a problem of approximating this density function. (Author)
Descriptors : (*CONTROL SYSTEMS, MATHEMATICAL MODELS), NONLINEAR SYSTEMS, STOCHASTIC PROCESSES, PERTURBATION THEORY, PROBABILITY DENSITY FUNCTIONS, ASYMPTOTIC SERIES, DIFFERENCE EQUATIONS, DECISION THEORY, APPROXIMATION(MATHEMATICS)
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE