Title :
An assessment of the minimum divergence criterion
Author :
Newmann, M.M. ; Sprevak, D.
Author_Institution :
Queen´´s University of Belfast, Belfast, Northern Ireland
fDate :
4/1/1980 12:00:00 AM
Abstract :
The criterion of minimum divergence was first presented in this journal a few years ago as a tool from which an algorithm may be derived for the estimation of the state of a discrete linear dynamical system subject to noisy disturbances. Recently, the criterion was used as the basis of an algorithm for simultaneous state-parameter estimation. We show in this note that from both theoretical and practical viewpoints, the principle of minimum divergence is likely to lead to estimators with unnecessarily poor performance.
Keywords :
Linear systems, stochastic discrete-time; State estimation; Covariance matrix; Equations; Filtering; Filters; Mathematics; Parameter estimation; Particle measurements; State estimation; Stochastic systems; Uncertainty;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1980.1102319