Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
Current issue: Aug 2017
Next issue: Nov 2017
Avg review time: 104 days


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


TRAFFIC STATS

1,766,597 unique visits
510,147 downloads
Since November 1, 2009



Robots online now
Yahoo! Slurp


SJR SCImago RANK

SCImago Journal & Country Rank


SEARCH ENGINES

aece.ro - Google Pagerank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 17 (2017)
 
     »   Issue 3 / 2017
 
     »   Issue 2 / 2017
 
     »   Issue 1 / 2017
 
 
 Volume 16 (2016)
 
     »   Issue 4 / 2016
 
     »   Issue 3 / 2016
 
     »   Issue 2 / 2016
 
     »   Issue 1 / 2016
 
 
 Volume 15 (2015)
 
     »   Issue 4 / 2015
 
     »   Issue 3 / 2015
 
     »   Issue 2 / 2015
 
     »   Issue 1 / 2015
 
 
 Volume 14 (2014)
 
     »   Issue 4 / 2014
 
     »   Issue 3 / 2014
 
     »   Issue 2 / 2014
 
     »   Issue 1 / 2014
 
 
  View all issues  


FEATURED ARTICLE

ABC Algorithm based Fuzzy Modeling of Optical Glucose Detection, SARACOGLU, O. G., BAGIS, A., KONAR, M., TABARU, T. E.
Issue 3/2016

AbstractPlus






LATEST NEWS

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Apr-04
We have the confirmation Advances in Electrical and Computer Engineering will be included in the EBSCO database.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

2017-Jan-30
We have the confirmation Advances in Electrical and Computer Engineering will be included in the Gale database.

2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

Read More »


    
 

  3/2011 - 3

Fault Tolerant Neural Network for ECG Signal Classification Systems

MERAH, M. See more information about MERAH, M. on SCOPUS See more information about MERAH, M. on IEEExplore See more information about MERAH, M. on Web of Science, OUAMRI, A. See more information about  OUAMRI, A. on SCOPUS See more information about  OUAMRI, A. on SCOPUS See more information about OUAMRI, A. on Web of Science, NAIT-ALI, A. See more information about  NAIT-ALI, A. on SCOPUS See more information about  NAIT-ALI, A. on SCOPUS See more information about NAIT-ALI, A. on Web of Science, KECHE, M. See more information about KECHE, M. on SCOPUS See more information about KECHE, M. on SCOPUS See more information about KECHE, M. on Web of Science
 
Click to see author's profile on 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 (1,855 KB) | Citation | Downloads: 1,064 | Views: 2,744

Author keywords
fault tolerant, artificial neural networks, hybrid backpropagation algorithms, medical diagnosis

References keywords
neural(19), networks(13), network(5), learning(5), fault(5), systems(4), algorithms(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2011-08-31
Volume 11, Issue 3, Year 2011, On page(s): 17 - 24
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.03003
Web of Science Accession Number: 000296186700003
SCOPUS ID: 80055082608

Abstract
Quick view
Full text preview
The aim of this paper is to apply a new robust hardware Artificial Neural Network (ANN) for ECG classification systems. This ANN includes a penalization criterion which makes the performances in terms of robustness. Specifically, in this method, the ANN weights are normalized using the auto-prune method. Simulations performed on the MIT - BIH ECG signals, have shown that significant robustness improvements are obtained regarding potential hardware artificial neuron failures. Moreover, we show that the proposed design achieves better generalization performances, compared to the standard back-propagation algorithm.


References | Cited By

Cited-By ISI Web of Science

Web of Science® Times Cited: 4 [View]
View record in Web of Science® [View]
View Related Records® [View]

Updated today


Cited-By CrossRef

SCOPUS® Times Cited: 5
View record in SCOPUS®
[Free preview]

Updated today

Cited-By CrossRef

[1] Detection of electrocardiogram characteristic points using lifting wavelet transform and Hilbert transform, Li, Hongqiang, Wang, Xiaofei, Transactions of the Institute of Measurement and Control, ISSN 0142-3312, Issue 5, Volume 35, 2013.
Digital Object Identifier: 10.1177/0142331212460720
[CrossRef]

[2] R-peaks detection based on stationary wavelet transform, Merah, M., Abdelmalik, T.A., Larbi, B.H., Computer Methods and Programs in Biomedicine, ISSN 0169-2607, Issue 3, Volume 121, 2015.
Digital Object Identifier: 10.1016/j.cmpb.2015.06.003
[CrossRef]

[3] A New Method for EEG Compressive Sensing, FIRA, M., GORAS, L., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 12, 2012.
Digital Object Identifier: 10.4316/AECE.2012.04011
[CrossRef] [Full text]

[4] 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]

Updated today

Disclaimer: All information displayed above was retrieved by using remote connections to respective databases. For the best user experience, we update all data by using background processes, and use caches in order to reduce the load on the servers we retrieve the information from. As we have no control on the availability of the database servers and sometimes the Internet connectivity may be affected, we do not guarantee the information is correct or complete. For the most accurate data, please always consult the database sites directly. Some external links require authentication or an institutional subscription.

Web of Science® is a registered trademark of Thomson Reuters, Scopus® is a registered trademark of Elsevier B.V., other product names, company names, brand names, trademarks and logos are the property of their respective owners.


Copyright ©2001-2017
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.




Website loading speed and performance optimization powered by: