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Titolo:
ESTIMATION OF MODEL QUALITY
Autore:
NINNESS B; GOODWIN GC;
Indirizzi:
UNIV NEWCASTLE,CTR IND CONTROL SCI CALLAGHAN NSW 2308 AUSTRALIA UNIV NEWCASTLE,DEPT ELECT & COMP ENGN CALLAGHAN NSW 2308 AUSTRALIA
Titolo Testata:
Automatica
fascicolo: 12, volume: 31, anno: 1995,
pagine: 1771 - 1797
SICI:
0005-1098(1995)31:12<1771:EOMQ>2.0.ZU;2-J
Fonte:
ISI
Lingua:
ENG
Soggetto:
INFORMATION-BASED COMPLEXITY; SET MEMBERSHIP UNCERTAINTY; CASE SYSTEM-IDENTIFICATION; WORST-CASE IDENTIFICATION; BOUNDED-PARAMETER MODELS; H-INFINITY; ROBUST IDENTIFICATION; ERROR-BOUNDS; NONPARAMETRIC UNCERTAINTY; NONLINEAR ALGORITHMS;
Keywords:
SYSTEM IDENTIFICATION; ESTIMATION THEORY; IDENTIFICATION ALGORITHMS; LEAST-SQUARES ESTIMATION; PARAMETER ESTIMATION; MODEL APPROXIMATION; PROCESS IDENTIFICATION; ERROR ESTIMATION; BOUNDED DISTURBANCES; STOCHASTIC MODELING;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
CompuMath Citation Index
Science Citation Index Expanded
Citazioni:
147
Recensione:
Indirizzi per estratti:
Citazione:
B. Ninness e G.C. Goodwin, "ESTIMATION OF MODEL QUALITY", Automatica, 31(12), 1995, pp. 1771-1797

Abstract

This paper provides an introduction to recent work on the problem of quantifying errors in the estimation of models for dynamic systems. This is a very large field. We therefore concentrate on approaches that have been motivated by the need for reliable models for control systemdesign. This will involve a discussion of efforts that go under the titles of 'estimation in H-x', 'worst-case estimation', 'estimation in l(1)' and 'stochastic embedding of undermodelling'. A central theme ofthis survey is to examine these new methods with reference to the classic bias/variance tradeoff in model structure selection.

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Documento generato il 29/11/20 alle ore 15:51:55