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JCR Impact Factor: 0.800
JCR 5-Year IF: 1.000
SCOPUS CiteScore: 2.0
Issues per year: 4
Current issue: May 2024
Next issue: Aug 2024
Avg review time: 57 days
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PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

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


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2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

2021-Jun-30
Clarivate Analytics published the InCites Journal Citations Report for 2020. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.221 (1.053 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.961.

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  4/2012 - 11

 HIGHLY CITED PAPER 

A New Method for EEG Compressive Sensing

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
 
View the paper record and citations in View the paper record and citations in Google Scholar
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (622 KB) | Citation | Downloads: 1,034 | Views: 4,516

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

References keywords
sensing(11), signal(7), information(6), processing(5), systems(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2012-11-30
Volume 12, Issue 4, Year 2012, On page(s): 71 - 76
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.04011
Web of Science Accession Number: 000312128400011
SCOPUS ID: 84872762175

Abstract
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The paper investigates the possibility of using compressive sensing techniques for the acquisition and reconstruction of EEG signals containing the evoked potential P300. A method of EEG compressive sensing based on the physiological correlation of EEG channels is proposed. The reconstruction of 55 EEG channels signals acquired by compressive sensing uses a dictionary consisting of EEG signals from other nine channels with normal acquisition.


References | Cited By

Cited-By Clarivate Web of Science

Web of Science® Times Cited: 6 [View]
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Cited-By SCOPUS

SCOPUS® Times Cited: 7
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Updated 3 days, 13 hours ago

Cited-By CrossRef

[1] Development of a Medical Care Terminal for Efficient Monitoring of Bedridden Subjects, Pereira, Filipe, Carvalho, Vítor, Soares, Filomena, Machado, José, Bezerra, Karolina, Silva, Rui, Matos, Demétrio, Journal of Engineering, ISSN 2314-4904, Issue , 2016.
Digital Object Identifier: 10.1155/2016/3591059
[CrossRef]

[2] Prediction and Detection of Ventricular Fibrillation Using Complex Features and AI-Based Classification, Fira, Monica, Costin, Hariton-Nicolae, Goras, Liviu, Applied Sciences, ISSN 2076-3417, Issue 7, Volume 14, 2024.
Digital Object Identifier: 10.3390/app14073050
[CrossRef]

[3] Combined Sparsifying Transforms for Compressive Image Fusion, WU, C., WANG, H., XU, X., ZHAO, L., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 13, 2013.
Digital Object Identifier: 10.4316/AECE.2013.04014
[CrossRef] [Full text]

[4] Research into a novel surface acoustic wave sensor signal-processing system based on compressive sensing and an observed-signal augmentation method based on secondary information prediction, Han, Wei, Bu, Xiongzhu, Song, Meiqiu, Huang, Xinhao, Measurement Science and Technology, ISSN 0957-0233, Issue 7, Volume 32, 2021.
Digital Object Identifier: 10.1088/1361-6501/abe3ab
[CrossRef]

[5] Multi-Channel Transcranial Direct Current Stimulation (tDCS) utilizing A.I. and IoT Technologies for Remote Tele-Treatment, Shum, Anthony, Li, C. K., Lak, Davis, 2020 IEEE 2nd International Workshop on System Biology and Biomedical Systems (SBBS), ISBN 978-1-6654-0460-0, 2020.
Digital Object Identifier: 10.1109/SBBS50483.2020.9314934
[CrossRef]

[6] Reconstruction of compressed sensed ECG signals using patient specific dictionaries, Fira, Monica, Goras, Liviu, Barabasa, Constantin, International Symposium on Signals, Circuits and Systems ISSCS2013, ISBN 978-1-4673-6143-9, 2013.
Digital Object Identifier: 10.1109/ISSCS.2013.6651246
[CrossRef]

Updated 3 days, 13 hours ago

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


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