Damping oscillatory integrals.
Page 1 Next
M. Cowling, S. Disney, G. Mauceri (1990)
Inventiones mathematicae
David McMichael (1993)
Mathematica Scandinavica
Reinhold Meise (1972)
Mathematische Annalen
Walter Eberhard, Gerhard Freiling (1974)
Mathematische Zeitschrift
Václav Finěk (2004)
Applications of Mathematics
In this paper, Daubechies wavelets on intervals are investigated. An analytic technique for evaluating various types of integrals containing the scaling functions is proposed; they are compared with classical techniques. Finally, these results are applied to two-point boundary value problems.
Jean-Paul Pier (1992)
Cahiers du séminaire d'histoire des mathématiques
Luca Brandolini, Leonardo Colzani (2000)
Annali della Scuola Normale Superiore di Pisa - Classe di Scienze
G. Kyriazis (2003)
Studia Mathematica
Let be a decomposition system for indexed over D, the set of dyadic cubes in , and a finite set E, and let be the corresponding dual functionals. That is, for every , . We study sufficient conditions on Θ,Θ̃ so that they constitute a decomposition system for Triebel-Lizorkin and Besov spaces. Moreover, these conditions allow us to characterize the membership of a distribution f in these spaces by the size of the coefficients , e ∈ E, I ∈ D. Typical examples of such decomposition systems...
T.W. Körner (1999)
The journal of Fourier analysis and applications [[Elektronische Ressource]]
Lal, Shyam, Nigam, Hare Krishna (2001)
International Journal of Mathematics and Mathematical Sciences
W. Haußmann, K. Jetter, B. Steinhaus (1985)
Mathematische Zeitschrift
Paul-André Meyer (1976)
Séminaire de probabilités de Strasbourg
Paul-André Meyer (1976)
Séminaire de probabilités de Strasbourg
Paul-André Meyer (1976)
Séminaire de probabilités de Strasbourg
Paul-André Meyer (1976)
Séminaire de probabilités de Strasbourg
Stefan Samko (1995)
Studia Mathematica
Jean Brossard (1988)
Inventiones mathematicae
Myriam Déchamps (1987)
Colloquium Mathematicae
Pierre Alquier (2008)
ESAIM: Probability and Statistics
We propose a feature selection method for density estimation with quadratic loss. This method relies on the study of unidimensional approximation models and on the definition of confidence regions for the density thanks to these models. It is quite general and includes cases of interest like detection of relevant wavelets coefficients or selection of support vectors in SVM. In the general case, we prove that every selected feature actually improves the performance of the estimator. In the case...
Allan Pinkus (2004)
Banach Center Publications
Approximation theory and functional analysis share many common problems and points of contact. One of the areas of mutual interest is that of density results. In this paper we briefly survey various methods and results in this area starting from work of Weierstrass and Riesz, and extending to more recent times.
Page 1 Next