Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.800
JCR 5-Year IF: 1.000
SCOPUS CiteScore: 2.0
Issues per year: 4
Current issue: Feb 2024
Next issue: May 2024
Avg review time: 78 days
Avg accept to publ: 48 days
APC: 300 EUR


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

2,498,026 unique visits
994,299 downloads
Since November 1, 2009



Robots online now
bingbot
Googlebot


SCOPUS CiteScore

SCOPUS CiteScore


SJR SCImago RANK

SCImago Journal & Country Rank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 24 (2024)
 
     »   Issue 1 / 2024
 
 
 Volume 23 (2023)
 
     »   Issue 4 / 2023
 
     »   Issue 3 / 2023
 
     »   Issue 2 / 2023
 
     »   Issue 1 / 2023
 
 
 Volume 22 (2022)
 
     »   Issue 4 / 2022
 
     »   Issue 3 / 2022
 
     »   Issue 2 / 2022
 
     »   Issue 1 / 2022
 
 
 Volume 21 (2021)
 
     »   Issue 4 / 2021
 
     »   Issue 3 / 2021
 
     »   Issue 2 / 2021
 
     »   Issue 1 / 2021
 
 
  View all issues  


FEATURED ARTICLE

Analysis of the Hybrid PSO-InC MPPT for Different Partial Shading Conditions, LEOPOLDINO, A. L. M., FREITAS, C. M., MONTEIRO, L. F. C.
Issue 2/2022

AbstractPlus






LATEST NEWS

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.

Read More »


    
 

  3/2021 - 1
View TOC | « Previous Article | Next Article »

 HIGHLY CITED PAPER 

Robust 2-bit Quantization of Weights in Neural Network Modeled by Laplacian Distribution

PERIC, Z. See more information about PERIC, Z. on SCOPUS See more information about PERIC, Z. on IEEExplore See more information about PERIC, Z. on Web of Science, DENIC, B. See more information about  DENIC, B. on SCOPUS See more information about  DENIC, B. on SCOPUS See more information about DENIC, B. on Web of Science, DINCIC, M. See more information about  DINCIC, M. on SCOPUS See more information about  DINCIC, M. on SCOPUS See more information about DINCIC, M. on Web of Science, NIKOLIC, J. See more information about NIKOLIC, J. on SCOPUS See more information about NIKOLIC, J. on SCOPUS See more information about NIKOLIC, J. 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 (1,299 KB) | Citation | Downloads: 1,225 | Views: 1,585

Author keywords
image classification, neural networks, quantization, signal to noise ratio, source coding

References keywords
neural(18), networks(14), learning(7), information(7), quantization(6), processing(6), systems(5), machine(5), deep(5), convolutional(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2021-08-31
Volume 21, Issue 3, Year 2021, On page(s): 3 - 10
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.03001
Web of Science Accession Number: 000691632000001
SCOPUS ID: 85114815185

Abstract
Quick view
Full text preview
Significant efforts are constantly involved in finding manners to decrease the number of bits required for quantization of neural network parameters. Although in addition to compression, in neural networks, the application of quantizer models that are robust to changes in the variance of input data is of great importance, to the best of authors knowledge, this topic has not been sufficiently researched so far. For that reason, in this paper we give preference to logarithmic companding scalar quantizer, which has shown the best robustness in high quality quantization of speech signals, modelled similarly as weights in neural networks, by Laplacian distribution. We explore its performance by performing the exact and asymptotic analysis for low resolution scenario with 2-bit quantization, where we draw firm conclusions about the usability of the exact performance analysis and design of our quantizer. Moreover, we provide a manner to increase the robustness of the quantizer we propose by involving additional adaptation of the key parameter. Theoretical and experimental results obtained by applying our quantizer in processing of neural network weights are very good matched, and, for that reason, we can expect that our proposal will find a way to practical implementation.


References | Cited By

Cited-By Clarivate Web of Science

Web of Science® Times Cited: 5 [View]
View record in Web of Science® [View]
View Related Records® [View]

Updated 2 days, 21 hours ago


Cited-By SCOPUS

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

Updated today

Cited-By CrossRef

[1] Two Novel Non-Uniform Quantizers with Application in Post-Training Quantization, Perić, Zoran, Aleksić, Danijela, Nikolić, Jelena, Tomić, Stefan, Mathematics, ISSN 2227-7390, Issue 19, Volume 10, 2022.
Digital Object Identifier: 10.3390/math10193435
[CrossRef]

[2] Iterative Algorithm for Parameterization of Two-Region Piecewise Uniform Quantizer for the Laplacian Source, Nikolić, Jelena, Aleksić, Danijela, Perić, Zoran, Dinčić, Milan, Mathematics, ISSN 2227-7390, Issue 23, Volume 9, 2021.
Digital Object Identifier: 10.3390/math9233091
[CrossRef]

[3] Performance of Post-Training Two-Bits Uniform and Layer-Wise Uniform Quantization for MNIST Dataset from the Perspective of Support Region Choice, Tomić, Stefan, Nikolić, Jelena, Perić, Zoran, Aleksić, Danijela, Gao, Hao, Mathematical Problems in Engineering, ISSN 1563-5147, Issue , 2022.
Digital Object Identifier: 10.1155/2022/1463094
[CrossRef]

[4] Whether the Support Region of Three-Bit Uniform Quantizer Has a Strong Impact on Post-Training Quantization for MNIST Dataset?, Nikolić, Jelena, Perić, Zoran, Aleksić, Danijela, Tomić, Stefan, Jovanović, Aleksandra, Entropy, ISSN 1099-4300, Issue 12, Volume 23, 2021.
Digital Object Identifier: 10.3390/e23121699
[CrossRef]

Updated 2 days, 21 hours ago

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 Clarivate Analytics, 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 ©2001-2024
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: 


DNS Made Easy