Multivariate trigonometric wavelet decompositions

J. Prestin; F. Sprengel

doi:10.1016/0898-1221(95)00094-1

Multivariate trigonometric wavelet decompositions

J. Prestin^*, F. Sprengel

^*Corresponding author for this work

Institute of Mathematics

University of Rostock

Abstract

Decomposition and reconstruction algorithms for nested spaces of multivariate trigonometric polynomials are described. The scaling functions of these spaces are chosen as fundamental polynomials of Lagrange interpolation. Their properties are crucial for the approach presented here. In particular, FFT-algorithms can be used efficiently.

Original language	English
Journal	Computers and Mathematics with Applications
Volume	30
Issue number	3-6
Pages (from-to)	169-182
Number of pages	14
ISSN	0898-1221
DOIs	https://doi.org/10.1016/0898-1221(95)00094-1
Publication status	Published - 01.01.1995

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10.1016/0898-1221(95)00094-1

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title = "Multivariate trigonometric wavelet decompositions",

abstract = "Decomposition and reconstruction algorithms for nested spaces of multivariate trigonometric polynomials are described. The scaling functions of these spaces are chosen as fundamental polynomials of Lagrange interpolation. Their properties are crucial for the approach presented here. In particular, FFT-algorithms can be used efficiently.",

author = "J. Prestin and F. Sprengel",

year = "1995",

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doi = "10.1016/0898-1221(95)00094-1",

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AU - Prestin, J.

AU - Sprengel, F.

PY - 1995/1/1

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N2 - Decomposition and reconstruction algorithms for nested spaces of multivariate trigonometric polynomials are described. The scaling functions of these spaces are chosen as fundamental polynomials of Lagrange interpolation. Their properties are crucial for the approach presented here. In particular, FFT-algorithms can be used efficiently.

AB - Decomposition and reconstruction algorithms for nested spaces of multivariate trigonometric polynomials are described. The scaling functions of these spaces are chosen as fundamental polynomials of Lagrange interpolation. Their properties are crucial for the approach presented here. In particular, FFT-algorithms can be used efficiently.

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DO - 10.1016/0898-1221(95)00094-1

M3 - Journal articles

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JO - Computers and Mathematics with Applications

JF - Computers and Mathematics with Applications

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Multivariate trigonometric wavelet decompositions

Abstract

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