Compressive sensing approach in the Hermite transform domain
type: Item
instance of: scholarly article
title: Compressive sensing approach in the Hermite transform domain
zbMATH Open document ID: 1395.94163
DOI: 10.1155/2015/286590
author: Srdjan S. Stankovic
author: Irena Orović
author: Ljubiša Stanković
published in: Mathematical Problems in Engineering
publication date: 2018-08-27T00:00:00Z
review text: Summary: Compressive sensing has attracted significant interest of researchers providing an alternative way to sample and reconstruct the signals. This approach allows us to recover the entire signal from just a small set of random samples, whenever the signal is sparse in certain transform domain. Therefore, exploring the possibilities of using different transform basis is an important task, needed to extend the field of compressive sensing applications. In this paper, a compressive sensing approach based on the Hermite transform is proposed. The Hermite transform by itself provides compressed signal representation based on a smaller number of Hermite coefficients compared to the signal length. Here, it is shown that, for a wide class of signals characterized by sparsity in the Hermite domain, accurate signal reconstruction can be achieved even if incomplete set of measurements is used. Advantages of the proposed method are demonstrated on numerical examples. The presented concept is generalized for the short-time Hermite transform and combined transform.
Mathematics Subject Classification ID: 94A12
zbMATH DE Number: 6925962
Wikidata QID: Q59117867
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2015/286590
OpenAlex ID: W2190221683
cites work: Efficient Compression of QRS Complexes Using Hermite Expansion
cites work: Compressed sensing
cites work: Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
description: scientific article; zbMATH DE number 6925962