DocumentCode
828492
Title
Necessary and sufficient conditions for local second-order identifiability
Author
Goodrich, R.L. ; Caines, P.E.
Author_Institution
ABT Associates, Incorporated, Cambridge, MA, USA
Volume
24
Issue
1
fYear
1979
fDate
2/1/1979 12:00:00 AM
Firstpage
125
Lastpage
127
Abstract
This note presents a new formulation and proof of the result the Hessian of the likelihood function of an observed process at the point
in a parameter space, computed under the assumption that the process is i.i.d. Gaussian, is asymptotically nonsingular if and only if
is locally second-order identifiable. That is to say, if and only if the parameters in a neighborhood of
are in one-to-one correspondence with the second-order statistics of the observed process.
in a parameter space, computed under the assumption that the process is i.i.d. Gaussian, is asymptotically nonsingular if and only if
is locally second-order identifiable. That is to say, if and only if the parameters in a neighborhood of
are in one-to-one correspondence with the second-order statistics of the observed process.Keywords
Hessian matrices; Parameter identification; maximum-likelihood (ML) estimation; Adaptive control; Convergence; Equations; Filters; Linear systems; Observers; Parameter estimation; Programmable control; Sufficient conditions; System identification;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.1979.1101953
Filename
1101953
Link To Document