Orthonormal, Moment Preserving Boundary Wavelet Scaling Functions in Python

Josefine Holm, Thomas Arildsen, M Nielsen, Steffen Lønsmann Nielsen

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

In this paper we derive an orthonormal basis of wavelet scaling functions for L2 ([0, 1]) motivated by the need for such a basis in the field of generalized sampling. A special property of this basis is that it includes carefully constructed boundary functions and it can be constructed with arbitrary smoothness. This construction makes assumptions about the signal outside the interval unnecessary. Furthermore, we provide a Python package implementing this wavelet decomposition. Wavelets defined on a bounded interval are widely used for signal analysis, compression, and for numerical solution of differential equations. We show that for many cases using the basis that we derive results in smaller error than the commonly used alternative.
Original languageEnglish
Article number2032
JournalSN Applied Sciences
Volume2
Issue number12
Number of pages9
ISSN2523-3971
DOIs
Publication statusPublished - Nov 2020

Fingerprint

Dive into the research topics of 'Orthonormal, Moment Preserving Boundary Wavelet Scaling Functions in Python'. Together they form a unique fingerprint.
  • BoundaryWavelets

    Holm, J., Lønsmann Nielsen, S. & Arildsen, T., 12 Feb 2019

    Research output: Non-textual formComputer programmeResearch

    Open Access
    File
    34 Downloads (Pure)

Cite this