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JCR Impact Factor: 0.699
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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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LATEST NEWS

2018-Jun-27
Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

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-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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  2/2012 - 9

A Method for Designing FIR Filters with Arbitrary Magnitude Characteristic Used for Modeling Human Audiogram

SZOPOS, E. See more information about SZOPOS, E. on SCOPUS See more information about SZOPOS, E. on IEEExplore See more information about SZOPOS, E. on Web of Science, NEAG, M. See more information about  NEAG, M. on SCOPUS See more information about  NEAG, M. on SCOPUS See more information about NEAG, M. on Web of Science, SARACUT, I. See more information about  SARACUT, I. on SCOPUS See more information about  SARACUT, I. on SCOPUS See more information about SARACUT, I. on Web of Science, HEDESIU, H. See more information about  HEDESIU, H. on SCOPUS See more information about  HEDESIU, H. on SCOPUS See more information about HEDESIU, H. on Web of Science, FESTILA, L. See more information about FESTILA, L. on SCOPUS See more information about FESTILA, L. on SCOPUS See more information about FESTILA, L. on Web of Science
 
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Download PDF pdficon (730 KB) | Citation | Downloads: 556 | Views: 279

Author keywords
discrete Fourier transforms, error analysis, FIR filter, interpolation and non-uniform sampling

References keywords
digital(7), filter(6), design(5), systems(4), circuits(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2012-05-30
Volume 12, Issue 2, Year 2012, On page(s): 51 - 56
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.02009
Web of Science Accession Number: 000305608000009
SCOPUS ID: 84865294072

Abstract
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This paper presents an iterative method for designing FIR filters that implement arbitrary magnitude characteristics, defined by the user through a set of frequency-magnitude points (frequency samples). The proposed method is based on the non-uniform frequency sampling algorithm. For each iteration a new set of frequency samples is generated, by processing the set used in the previous run; this implies changing the samples location around the previous frequency values and adjusting their magnitude through interpolation. If necessary, additional samples can be introduced, as well. After each iteration the magnitude characteristic of the resulting filter is determined by using the non-uniform DFT and compared with the required one; if the errors are larger than the acceptable levels (set by the user) a new iteration is run; the length of the resulting filter and the values of its coefficients are also taken into consideration when deciding a re-run. To demonstrate the efficiency of the proposed method a tool for designing FIR filters that match human audiograms was implemented in LabVIEW. It was shown that the resulting filters have smaller coefficients than the standard one, and can also have lower order, while the errors remain relatively small.


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

[1] A. Antoniou, "Digital Signal Processing", McGraw Hill, pp. 425-458, 2005.

[2] T. W. Parks, C. S. Burrus, "Digital filter design", John Wiley & Sons Inc., pp. 33-44, 1987.

[3] L. R. Rabiner, R. W. Schafer, "Recursive and nonrecursive realizations of digital filters designed by frequency sampling techniques", IEEE Trans. on Audio and Electroacoustics, 1971
[CrossRef] [SCOPUS Times Cited 51]


[4] H. Samueli, "On the design of optimal equiripple FIR digital filters for data transmission application", IEEE Trans. on Circuits and Systems, 1988
[CrossRef] [Web of Science Times Cited 59] [SCOPUS Times Cited 63]


[5] G. J. Dolecek "Demo Program for Frequency Sampling FIR Filter Design Method", Frontiers in Education Conference, 2010
[CrossRef] [SCOPUS Times Cited 1]


[6] J. Huopaniemi, M. Karjalainen, "HRTF filter design based on auditory criteria", Proc. Nordic Acoustical Meeting, 1996.

[7] Y. Lian, Y. Wei, "A computationally efficient nonuniform FIR digital filter bank for hearing aids", IEEE Trans. on Circuits and Systems, 2005
[CrossRef] [Web of Science Times Cited 35] [SCOPUS Times Cited 46]


[8] E. Szopos, M. Topa, L. Festila, H. Hedesiu, "FIR synthesis of the human hearing mechanism response", Acta Technica Napocensis, Electronics and Telecommunications, pp. 41-44, 2010.

[9] L. R. Rabiner, "Techniques for designing finite-duration impulse-response digital filters", IEEE Trans. on Audio and Electroacoustics, 1971
[CrossRef] [SCOPUS Times Cited 49]


[10] I. Gohberg, V. Olshevsky, "The fast generalized Parker-Traub algorithm for inversion of Vandermonde and related matrices", Journal of Complexity, 1997
[CrossRef] [Web of Science Times Cited 30] [SCOPUS Times Cited 32]


[11] A. Eisinberg, G. Fedele, "On the inversion of the Vandermonde matrix", Applied Mathematics and Computation, Elsevier, 2006
[CrossRef] [Web of Science Times Cited 37] [SCOPUS Times Cited 42]


[12] M. A. De Jesus, M. Teixeira, L. Vicente, Y. Rodriguez, "Nonuniform discrete short-time Fourier transform a Goertzel filter bank versus a FIR filtering approach", IEEE International Midwest Symposium on Circuits and Systems, 2007
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 4]


[13] S. Bagchi, S. K. Mitra, "The nonuniform discrete Fourier transform and its applications in filter design: Part I-1-D", IEEE Trans. On Circuits and Systems-II: Analog and Digital Signal Processing, 1996
[CrossRef] [Web of Science Times Cited 24] [SCOPUS Times Cited 30]


[14] O. O. Khalifa, M. H. Makhtar, M. S. Baharom, "Hearing aids system for impaired people", International Journal of Computing & Information Sciences, 2004.

[15] E. Szopos, H. Hedesiu, "LabVIEW FPGA based noise cancelling using the LMS adaptive algorithm", Acta Technica Napocensis, Electronics and Telecommunications, pp. 5-8, 2009.



References Weight

Web of Science® Citations for all references: 186 TCR
SCOPUS® Citations for all references: 318 TCR

Web of Science® Average Citations per reference: 12 ACR
SCOPUS® Average Citations per reference: 20 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 2018-10-16 22:53 in 70 seconds.




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


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