Identification of dynamic systems from noisy data: the case m *=n-1

Author

Anderson, B.D.O. ; Deistler, M.

Author_Institution

Dept. of Syst. Eng., Australian Nat. Univ., Canberra, ACT, Australia

fYear

1991

fDate

11-13 Dec 1991

Firstpage

1674

Abstract

Linear dynamic errors-in-variables (or factor) models in the framework of stationary processes are considered. The noise process is assumed to have a diagonal spectral density. The relation between the (population) second moments of the observations and the system and noise characteristics is analyzed; of particular interest are the number of equations (or the number of factors) and a description of the set of all systems compatible with the second moments of the observations. Emphasis is placed on the case which can be reduced to a single factor. The problems considered arise in the context of identification and precede estimation

Keywords

identification; linear systems; noise; spectral analysis; diagonal spectral density; dynamic systems identification; linear dynamic errors-in-variables models; linear systems; noise characteristics; noisy data; second moments; stationary processes; Computer aided software engineering; Econometrics; Encoding; Equations; Linear systems; Noise generators; Operations research; Predictive models; Psychometric testing; Statistical analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1991., Proceedings of the 30th IEEE Conference on

Conference_Location

Brighton

Print_ISBN

0-7803-0450-0

Type

conf

DOI

10.1109/CDC.1991.261692

Filename

261692