Generalized Sampling in Julia

Robert Dahl Jacobsen; Morten Nielsen; Morten Grud Rasmussen

doi:10.5334/jors.157

Generalized Sampling in Julia

Journal of Open Research Software

Volume 5 (2017): Issue 1

By: Robert Dahl Jacobsen , Morten Nielsen and Morten Grud Rasmussen

Open Access

|Apr 2017

Abstract

Generalized sampling is a numerically stable framework for obtaining reconstructions of signals in different bases and frames from their samples. For example, one can use wavelet bases for reconstruction given frequency measurements.

In this paper, we will introduce a carefully documented toolbox for performing generalized sampling in Julia. Julia is a new language for technical computing with focus on performance, which is ideally suited to handle the large size problems often encountered in generalized sampling. The toolbox provides specialized solutions for the setup of Fourier bases and wavelets.

The performance of the toolbox is compared to existing implementations of generalized sampling in MATLAB.

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Articles in this issue

DOI: https://doi.org/10.5334/jors.157 | Journal eISSN: 2049-9647

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Language: English

Submitted on: Nov 29, 2016

Accepted on: Mar 23, 2017

Published on: Apr 20, 2017

Published by: Ubiquity Press

In partnership with: Paradigm Publishing Services

Publication frequency: 1 issue per year

Keywords:

Generalized Sampling,

Julia,

Fourier basis,

Wavelets

© 2017 Robert Dahl Jacobsen, Morten Nielsen, Morten Grud Rasmussen, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 5 (2017): Issue 1