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JCR Impact Factor: 0.700
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Current issue: Aug 2024
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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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2024-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2023. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.700 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.600.

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.

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  3/2012 - 2

 HIGHLY CITED PAPER 

Parallel-Hierarchical Computing System for Multi-Level Transformation of Masked Digital Signals

YAROVYY, A. A. See more information about YAROVYY, A. A. on SCOPUS See more information about YAROVYY, A. A. on IEEExplore See more information about YAROVYY, A. A. on Web of Science, TIMCHENKO, L. I. See more information about  TIMCHENKO, L. I. on SCOPUS See more information about  TIMCHENKO, L. I. on SCOPUS See more information about TIMCHENKO, L. I. on Web of Science, KOKRIATSKAIA, N. I. See more information about KOKRIATSKAIA, N. I. on SCOPUS See more information about KOKRIATSKAIA, N. I. on SCOPUS See more information about KOKRIATSKAIA, N. I. on Web of Science
 
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Download PDF pdficon (1,616 KB) | Citation | Downloads: 935 | Views: 4,512

Author keywords
codes, computer science, image processing, parallel processing, transform coding

References keywords
yarovyy(11), processing(10), parallel(8), timchenko(7), hierarchical(7), kozhemyako(6), digital(6), transformation(5), systems(5), signal(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2012-08-31
Volume 12, Issue 3, Year 2012, On page(s): 13 - 20
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.03002
Web of Science Accession Number: 000308290500002
SCOPUS ID: 84865841747

Abstract
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Paper deals with organization principles of parallel-hierarchical (PH) transform for multistage perception and processing, compression and recognition of information in computational systems which make use of computational scheme similar to neural. Unified methodological approach was developed for analysis of parallel processes. This approach considers influence of structural hierarchy in dynamics. It tracks processes of spatial areas transformation of correlated and generation of uncorrelated in time elements of generated PH network, at the time of transition of the network from one stable stage to another. The main feature of the proposed method is the studying of the dynamics of spatial-correlated procedure for transformation between current and output units in PH network. This procedure gives an opportunity to present processing in PH network as the process of parallel-sequential transformation of diverse image components and consideration of temporal characteristics of transformation. The features analysis of structural-functional organization of networking model of PH transformation of the information environments and corresponding masks generation methods is realized in the given research. On the base of research carried out the method of optimized masks formation while information coding in PH transformation is proposed. The software package, characterized by increased efficiency of direct and reverse PH transformation is developed.


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Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 8
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Cited-By CrossRef

[1] Modelling of Piling Technology by Vibroimpact Device with Hydropulse Drive, Ivanchuk, Yaroslav, Manzhilevskyy, Oleksandr, Belzetskyi, Ruslan, Zamkovyi, Oleksandr, Pavlovych, Roman, Scientific Horizons, ISSN 2709-8877, Issue 1, Volume 25, 2022.
Digital Object Identifier: 10.48077/scihor.25(1).2022.9-20
[CrossRef]

[2] Section method for monitoring the surface shape of a radiation spot in real time, Tymchenko, Leonid, Kokriatska, Natalia, Tverdomed, Volodymyr, Kutaev, Yurii, Zhuk, Dmytro, 2022 International Conference on Development and Application Systems (DAS), ISBN 978-1-6654-8162-5, 2022.
Digital Object Identifier: 10.1109/DAS54948.2022.9786114
[CrossRef]

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


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