A software companion for compressively sensed time–frequency processing of sparse nonstationary signals

A software companion for compressively sensed time–frequency processing of sparse nonstationary signals

Compressive sensing is a computational framework for acquisition and processing of sparse signals at sampling rates below the rates mandated by the Nyquist sampling theorem. In this paper, we present seven MATLAB functions for compressive sensing based time–frequency processing of sparse nonstationa...

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Main Authors: Ervin Sejdić, Irena Orović, Srdjan Stanković
Format: Article
Language:English
Published: Elsevier 2018-07-01
Series:SoftwareX
Online Access:http://www.sciencedirect.com/science/article/pii/S2352711017300365
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spelling doaj-ce87bb8596e945839b19ad1dbb2444f52020-11-25T01:46:40ZengElsevierSoftwareX2352-71102018-07-018910A software companion for compressively sensed time–frequency processing of sparse nonstationary signalsErvin Sejdić0Irena Orović1Srdjan Stanković2Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15261, USA; Corresponding author.Faculty of Electrical Engineering, University of Montenegro, Podgorica, MontenegroFaculty of Electrical Engineering, University of Montenegro, Podgorica, MontenegroCompressive sensing is a computational framework for acquisition and processing of sparse signals at sampling rates below the rates mandated by the Nyquist sampling theorem. In this paper, we present seven MATLAB functions for compressive sensing based time–frequency processing of sparse nonstationary signals. These functions are developed to reproduce figures in our companion review paper. Keywords: Compressive sensing, Time–frequency analysis, Nonstationary signalshttp://www.sciencedirect.com/science/article/pii/S2352711017300365
collection DOAJ
language English
format Article
sources DOAJ
author Ervin Sejdić
Irena Orović
Srdjan Stanković
spellingShingle Ervin Sejdić
Irena Orović
Srdjan Stanković
A software companion for compressively sensed time–frequency processing of sparse nonstationary signals
SoftwareX
author_facet Ervin Sejdić
Irena Orović
Srdjan Stanković
author_sort Ervin Sejdić
title A software companion for compressively sensed time–frequency processing of sparse nonstationary signals
title_short A software companion for compressively sensed time–frequency processing of sparse nonstationary signals
title_full A software companion for compressively sensed time–frequency processing of sparse nonstationary signals
title_fullStr A software companion for compressively sensed time–frequency processing of sparse nonstationary signals
title_full_unstemmed A software companion for compressively sensed time–frequency processing of sparse nonstationary signals
title_sort software companion for compressively sensed time–frequency processing of sparse nonstationary signals
publisher Elsevier
series SoftwareX
issn 2352-7110
publishDate 2018-07-01
description Compressive sensing is a computational framework for acquisition and processing of sparse signals at sampling rates below the rates mandated by the Nyquist sampling theorem. In this paper, we present seven MATLAB functions for compressive sensing based time–frequency processing of sparse nonstationary signals. These functions are developed to reproduce figures in our companion review paper. Keywords: Compressive sensing, Time–frequency analysis, Nonstationary signals
url http://www.sciencedirect.com/science/article/pii/S2352711017300365
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AT irenaorovic asoftwarecompanionforcompressivelysensedtimefrequencyprocessingofsparsenonstationarysignals
AT srdjanstankovic asoftwarecompanionforcompressivelysensedtimefrequencyprocessingofsparsenonstationarysignals
AT ervinsejdic softwarecompanionforcompressivelysensedtimefrequencyprocessingofsparsenonstationarysignals
AT irenaorovic softwarecompanionforcompressivelysensedtimefrequencyprocessingofsparsenonstationarysignals
AT srdjanstankovic softwarecompanionforcompressivelysensedtimefrequencyprocessingofsparsenonstationarysignals
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