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  4/2010 - 4

 HIGH-IMPACT PAPER 

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: 2,130 | Views: 5,954

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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[30] Temporary on-line reference link removed - see the PDF document

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[CrossRef] [PubMed] [Web of Science Times Cited 292] [SCOPUS Times Cited 376]




References Weight

Web of Science® Citations for all references: 32,418 TCR
SCOPUS® Citations for all references: 42,939 TCR

Web of Science® Average Citations per reference: 853 ACR
SCOPUS® Average Citations per reference: 1,130 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 2022-08-06 16:38 in 119 seconds.




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