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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
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ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2010 - 4

On ECG Compressed Sensing using Specific Overcomplete Dictionaries

FIRA, M. See more information about FIRA, M. on SCOPUS See more information about FIRA, M. on IEEExplore See more information about FIRA, M. on Web of Science, GORAS, L. See more information about  GORAS, L. on SCOPUS See more information about  GORAS, L. on SCOPUS See more information about GORAS, L. on Web of Science, BARABASA, C. See more information about  BARABASA, C. on SCOPUS See more information about  BARABASA, C. on SCOPUS See more information about BARABASA, C. on Web of Science, CLEJU, N. See more information about CLEJU, N. on SCOPUS See more information about CLEJU, N. on SCOPUS See more information about CLEJU, N. on Web of Science
 
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Download PDF pdficon (1,859 KB) | Citation | Downloads: 1,693 | Views: 4,100

Author keywords
compressed sensing, biomedical signal processing, electrocardiography, pursuit algorithms, signal processing algorithms

References keywords
signal(12), wavelet(6), sensing(6), processing(6), biomed(6), tbme(5), signals(5), sampling(5), classification(5), science(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2010-11-30
Volume 10, Issue 4, Year 2010, On page(s): 23 - 28
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.04004
Web of Science Accession Number: 000284782700004
SCOPUS ID: 78649711600

Abstract
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The paper presents a number of results regarding the construction of specific overcomplete dictionaries for ECG compressed sensing (CS). The dictionaries were built using normal and patological cardiac patterns extracted from 24 recordings of the MIT-BIH Arrhythmia Database. It has been shown that the compression results obtained using the CS concept based on specific dictionaries are better that those using the wavelet overcomplete dictionaries. Starting from the concept of sparse signal with respect to a given overcomplete dictionary the paper present several results regarding the possibility of simple pattern classification as well.


References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 17,624 TCR
SCOPUS® Citations for all references: 21,163 TCR

Web of Science® Average Citations per reference: 464 ACR
SCOPUS® Average Citations per reference: 557 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2017-04-30 07:18 in 252 seconds.




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