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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
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Next issue: Nov 2017
Avg review time: 108 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


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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
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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.

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2016-Dec-17
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  2/2016 - 11

Quantitative Analysis of Memristance Defined Exponential Model for Multi-bits Titanium Dioxide Memristor Memory Cell

DAOUD, A. A. D. See more information about DAOUD, A. A. D. on SCOPUS See more information about DAOUD, A. A. D. on IEEExplore See more information about DAOUD, A. A. D. on Web of Science, DESSOUKI, A. A. S. See more information about  DESSOUKI, A. A. S. on SCOPUS See more information about  DESSOUKI, A. A. S. on SCOPUS See more information about DESSOUKI, A. A. S. on Web of Science, ABUELENIN, S. M. See more information about ABUELENIN, S. M. on SCOPUS See more information about ABUELENIN, S. M. on SCOPUS See more information about ABUELENIN, S. 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 (1,465 KB) | Citation | Downloads: 199 | Views: 622

Author keywords
analytical models, memristors, nonvolatile memory, SPICE, tunneling

References keywords
memristor(20), circuits(11), systems(9), model(6), devices(5), spice(4), physics(4), modeling(4), memristive(4), device(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-05-31
Volume 16, Issue 2, Year 2016, On page(s): 75 - 84
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.02011
Web of Science Accession Number: 000376996100011
SCOPUS ID: 84974855611

Abstract
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The ability to store multiple bits in a single memristor based memory cell is a key feature for high-capacity memory packages. Studying multi-bit memristor circuits requires high accuracy in modelling the memristance change. A memristor model based on a novel definition of memristance is proposed. A design of a single memristor memory cell using the proposed model for the platinum electrodes titanium dioxide memristor is illustrated. A specific voltage pulse is used with varying its parameters (amplitude or pulse width) to store different number of states in a single memristor. New state variation parameters associated with the utilized model are provided and their effects on write and read processes of memristive multi-states are analysed. PSPICE simulations are also held, and they show a good agreement with the data obtained from the analysis.


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


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