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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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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.

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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.

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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
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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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  1/2015 - 3

 HIGHLY CITED PAPER 

Sparse FIR Filter Design Based on Simulated Annealing Algorithm

WU, C. See more information about WU, C. on SCOPUS See more information about WU, C. on IEEExplore See more information about WU, C. on Web of Science, XU, X. See more information about  XU, X. on SCOPUS See more information about  XU, X. on SCOPUS See more information about XU, X. on Web of Science, ZHANG, X. See more information about  ZHANG, X. on SCOPUS See more information about  ZHANG, X. on SCOPUS See more information about ZHANG, X. on Web of Science, ZHAO, L. See more information about ZHAO, L. on SCOPUS See more information about ZHAO, L. on SCOPUS See more information about ZHAO, L. on Web of Science
 
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Download PDF pdficon (806 KB) | Citation | Downloads: 1,100 | Views: 3,065

Author keywords
digital filter design, simulated annealing, sparse FIR filter

References keywords
design(12), signal(10), processing(10), filters(10), systems(8), sparse(8), response(7), filter(7), circuits(7), simulated(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2015-02-28
Volume 15, Issue 1, Year 2015, On page(s): 17 - 22
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.01003
Web of Science Accession Number: 000352158600003
SCOPUS ID: 84924766096

Abstract
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Design of sparse finite impulse response (FIR) filter is of great importance to reduce the implementation cost. However, design of sparse FIR filter under the prescribed constraints is a highly non-convex problem. Traditional methods generally relax the non-convex design problem to a convex one, which leads the obtained solutions suboptimal. In this paper, the non-convex design problem is modeled as a combinatorial optimization problem and an algorithm based on simulated annealing (SA) is presented to solve it. At each stage of the proposed algorithm, with a fixed sparsity of the filter coefficients, SA is employed for finding the possible sparse pattern of the FIR filter that satisfies the prescribed constraints. Once the design constraints have been satisfied, the sparsity is added by one and the algorithm moves to the next stage. The algorithm successively increases the sparsity of the filter coefficients until no sparser solution could be obtained. The proposed algorithm is evaluated by two sets of examples, and better results can be achieved than other existing algorithms.


References | Cited By  «-- Click to see who has cited this paper

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[CrossRef] [Web of Science Times Cited 79] [SCOPUS Times Cited 85]


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[CrossRef] [Web of Science Times Cited 20] [SCOPUS Times Cited 21]


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[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 9]


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[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 7]


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[CrossRef] [SCOPUS Times Cited 355]


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[CrossRef] [Web of Science Times Cited 19648] [SCOPUS Times Cited 24961]


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[CrossRef] [SCOPUS Times Cited 45]


[15] C. Rusu, and B. Dumitrescu, "Iterative reweighted l1 design of sparse fir filters," Signal Processing, vol. 92, no. 4, pp. 905-911, 2012.
[CrossRef] [Web of Science Times Cited 53] [SCOPUS Times Cited 65]


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[17] A. Jiang, H. K. Kwan, and Y. Zhu, "Peak-Error-Constrained Sparse FIR Filter Design Using Iterative SOCP," IEEE Transactions on Signal Processing, vol. 60, no. 8, pp. 4035-4044, 2012.
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[23] X. Du, L. Cheng, and D. Chen, "A simulated annealing algorithm for sparse recovery by l0 minimization," Neurocomputing, vol. 131, pp. 98-104, 2014.
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[28] J. F. Sturm, "Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones," Optimization methods and software, vol. 11, no. 1-4, pp. 625-653, 1999.
[CrossRef] [Web of Science Times Cited 5055] [SCOPUS Times Cited 5969]




References Weight

Web of Science® Citations for all references: 59,279 TCR
SCOPUS® Citations for all references: 73,436 TCR

Web of Science® Average Citations per reference: 2,044 ACR
SCOPUS® Average Citations per reference: 2,532 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-11-22 02:13 in 180 seconds.




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