AustralieFrV1, PascalFrancis, Corpus, bibRecord, 006291

A note on the wavelet oracle

Identifieur interne : 006291 ( PascalFrancis/Corpus ); précédent : 006290; suivant : 006292

A note on the wavelet oracle

Auteurs : P. Hall ; G. Kerkyacharian ; D. Picard

Source :

Statistics & probability letters [ 0167-7152 ] ; 1999.

RBID : Pascal:99-0402177

Descripteurs français

Pascal (Inist)
- Méthode optimisation, Transformation ondelette, Analyse variance.

English descriptors

KwdEn :
- Optimization method, Variance analysis, Wavelet transformation.

Abstract

The extent to which wavelet function estimators achieve benchmark levels of performance is sometimes described in terms of our ability to interpret a mythical oracle, who has access to the "truth' about the target function. Since he is so wise, he is able to threshold in an optimal manner - that is, to include a term in the empirical wavelet expansion if and only if the square of the corresponding true coefficient is larger than the variance of its estimate. In this note we show that if thresholding is performed in blocks then, for piecewise-smooth functions, we can achieve the same first-order mean-square performance as the oracle, right down to the constant factor, for fixed, piecewise-smooth functions.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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A06				`@2 4`
A08	`01`	`1`	`ENG`	`@1 A note on the wavelet oracle`
A11	`01`	`1`		`@1 HALL (P.)`
A11	`02`	`1`		`@1 KERKYACHARIAN (G.)`
A11	`03`	`1`		`@1 PICARD (D.)`
A14	`01`			`@1 Centre for Mathematics and its Applications, Australian National University @2 Canberra, ACT 0260 @3 AUS @Z 1 aut. @Z 2 aut. @Z 3 aut.`
A14	`02`			`@1 Faculté Mathematiques et Informatiques, Université de Picardie, 33 rue Saint-Leu @2 80039 Amiens @3 FRA @Z 2 aut.`
A14	`03`			`@1 Département de Mathematiques, Université de Paris VII @2 75251 Paris @3 FRA @Z 3 aut.`
A20				`@1 415-420`
A21				`@1 1999`
A23	`01`			`@0 ENG`
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A44				`@0 0000 @1 © 1999 INIST-CNRS. All rights reserved.`
A45				`@0 9 ref.`
A47	`01`	`1`		`@0 99-0402177`
A60				`@1 P`
A61				`@0 A`
A64	`01`	`1`		`@0 Statistics & probability letters`
A66	`01`			`@0 NLD`
C01	`01`		`ENG`	@0 The extent to which wavelet function estimators achieve benchmark levels of performance is sometimes described in terms of our ability to interpret a mythical oracle, who has access to the "truth' about the target function. Since he is so wise, he is able to threshold in an optimal manner - that is, to include a term in the empirical wavelet expansion if and only if the square of the corresponding true coefficient is larger than the variance of its estimate. In this note we show that if thresholding is performed in blocks then, for piecewise-smooth functions, we can achieve the same first-order mean-square performance as the oracle, right down to the constant factor, for fixed, piecewise-smooth functions.
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C03	`01`	`X`	`FRE`	`@0 Méthode optimisation @5 01`
C03	`01`	`X`	`ENG`	`@0 Optimization method @5 01`
C03	`01`	`X`	`SPA`	`@0 Método optimización @5 01`
C03	`02`	`X`	`FRE`	`@0 Transformation ondelette @5 02`
C03	`02`	`X`	`ENG`	`@0 Wavelet transformation @5 02`
C03	`02`	`X`	`SPA`	`@0 Transformación ondita @5 02`
C03	`03`	`X`	`FRE`	`@0 Analyse variance @5 03`
C03	`03`	`X`	`ENG`	`@0 Variance analysis @5 03`
C03	`03`	`X`	`SPA`	`@0 Análisis variancia @5 03`
N21				`@1 256`

Format Inist (serveur)

NO :	PASCAL 99-0402177 INIST
ET :	A note on the wavelet oracle
AU :	HALL (P.); KERKYACHARIAN (G.); PICARD (D.)
AF :	Centre for Mathematics and its Applications, Australian National University/Canberra, ACT 0260/Australie (1 aut., 2 aut., 3 aut.); Faculté Mathematiques et Informatiques, Université de Picardie, 33 rue Saint-Leu/80039 Amiens/France (2 aut.); Département de Mathematiques, Université de Paris VII/75251 Paris/France (3 aut.)
DT :	Publication en série; Niveau analytique
SO :	Statistics & probability letters; ISSN 0167-7152; Coden SPLTDC; Pays-Bas; Da. 1999; Vol. 43; No. 4; Pp. 415-420; Bibl. 9 ref.
LA :	Anglais
EA :	The extent to which wavelet function estimators achieve benchmark levels of performance is sometimes described in terms of our ability to interpret a mythical oracle, who has access to the "truth' about the target function. Since he is so wise, he is able to threshold in an optimal manner - that is, to include a term in the empirical wavelet expansion if and only if the square of the corresponding true coefficient is larger than the variance of its estimate. In this note we show that if thresholding is performed in blocks then, for piecewise-smooth functions, we can achieve the same first-order mean-square performance as the oracle, right down to the constant factor, for fixed, piecewise-smooth functions.
CC :	001A02H02H; 001A02H02I
FD :	Méthode optimisation; Transformation ondelette; Analyse variance
ED :	Optimization method; Wavelet transformation; Variance analysis
SD :	Método optimización; Transformación ondita; Análisis variancia
LO :	INIST-19178.354000085331280120
ID :	99-0402177

Links to Exploration step

Pascal:99-0402177

Le document en format XML

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A note on the wavelet oracle

A note on the wavelet oracle

Source :

Descripteurs français

English descriptors

Abstract

Notice en format standard (ISO 2709)

Format Inist (serveur)

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri