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Titolo:
COMMON FACTOR DETECTION AND ESTIMATION
Autore:
STOICA P; SODERSTROM T;
Indirizzi:
UPPSALA UNIV,DEPT TECHNOL,SYST & CONTROL GRP,POB 27 S-75103 UPPSALA SWEDEN UPPSALA UNIV,DEPT TECHNOL,SYST & CONTROL GRP S-75103 UPPSALA SWEDEN
Titolo Testata:
Automatica
fascicolo: 5, volume: 33, anno: 1997,
pagine: 985 - 989
SICI:
0005-1098(1997)33:5<985:CFDAE>2.0.ZU;2-G
Fonte:
ISI
Lingua:
ENG
Soggetto:
IDENTIFICATION;
Keywords:
COMMON FACTORS; DETECTION; ESTIMATION; MAXIMUM LIKELIHOOD METHODS; HYPOTHESIS TESTING; SYSTEM IDENTIFICATION;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
CompuMath Citation Index
Science Citation Index Expanded
Citazioni:
8
Recensione:
Indirizzi per estratti:
Citazione:
P. Stoica e T. Soderstrom, "COMMON FACTOR DETECTION AND ESTIMATION", Automatica, 33(5), 1997, pp. 985-989

Abstract

The paper introduces a noniterative maximum likelihood (ML) based approach for the detection and estimation of the greatest common divisor of two given polynomials, the coefficients of which are assumed to have a normal distribution with a consistently estimable covariance matrix. It then goes on to show how this approach can be used to derive a noniterative ML method for estimating the orders and parameters of difference equation models with autoregressive residuals. Numerical examples are included to illustrate the performance of the proposed methodology.

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Documento generato il 11/08/20 alle ore 15:49:03