Wavelet Design

This is an overview of our wavelet related work.

Matched scalar wavelet design

The design of scalar wavelets for matching it to prototype signals.

Orthogonal scalar wavelet design
We design orthogonal wavelets such that they have a sparse representation in the wavelet domain for a prototype signal.

Publications: Software:

We have released the software covering the examples in the Circuits, systems, and signal processing 2018 paper, and this software is available for download on Zenodo. You can find a complete MATLAB implementation there.


Multiwavelet design

The design of multiwavelets for added flexibility compared to scalar wavelets. In principle this would function for multivariate signals, but one also can split univariate timeseries in multiple phases.

Multiwavelet design with balanced vanishing moments
We design multiwavelets such that they have a sparse representation in the wavelet domain for a prototype signal. In the case that the prototype signal is a univariate signal, it is important to have balanced vanishing moments. These are enforced by the parameterization.

Publications:


Wavelet approximation

The approximation of wavelet function for implementenation in analog circuits.

Wavelet approximation for implementation in the analog domain
As part of the BioSens project we approximated wavelets by continuous-time linear systems, for implementation in analog circuits to ensure ultra-low power.

Publications:


Wavelet applications

Various applications of wavelet theory.

Biomedical applications of wavelets
Publications: