Title :
Observability and fisher information matrix in nonlinear regression
Author :
Jauffret, Claude
Author_Institution :
Univ. du Sud Toulon-Var Batiment X, La Garde
fDate :
4/1/2007 12:00:00 AM
Abstract :
This paper is devoted to the link between the Fisher information matrix (FIM) invertibility and the observability of a parameter to be estimated in a nonlinear regression problem.
Keywords :
information theory; matrix algebra; regression analysis; Fisher information matrix; nonlinear regression problem; parameter estimation; Additive noise; Closed-form solution; Integral equations; Mathematics; Motion measurement; Noise measurement; Observability; Parameter estimation; Signal detection; Signal processing algorithms;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
DOI :
10.1109/TAES.2007.4285368
