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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

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 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.

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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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  3/2011 - 6

A Combined Feedback and Noise Cancellation Algorithm for Binaural Hearing Aids

LEE, H.-W. See more information about LEE, H.-W. on SCOPUS See more information about LEE, H.-W. on IEEExplore See more information about LEE, H.-W. on Web of Science, JEON, M.-Y. See more information about JEON, M.-Y. on SCOPUS See more information about JEON, M.-Y. on SCOPUS See more information about JEON, M.-Y. on Web of Science
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 (726 KB) | Citation | Downloads: 832 | Views: 3,569

Author keywords
hearing aids, feedback, noise reduction, acoustic beam, microphone array

References keywords
hearing(14), aids(14), feedback(12), processing(7), cancellation(7), adaptive(7), speech(5), signal(5), audio(4), acoustic(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2011-08-31
Volume 11, Issue 3, Year 2011, On page(s): 35 - 40
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.03006
Web of Science Accession Number: 000296186700006
SCOPUS ID: 80055079154

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This paper proposes an adaptive algorithm for the combined acoustic feedback and noise cancellation in the binaural hearing aids. The proposed algorithm is based on dual microphones for feedback cancellation and the beamforming method for noise cancellation. The coefficients of feedback canceller are updated after subtracting the speech signal from the input signal by dual microphones. And the noise canceller reduces the noise signal in the residual signal excluding the speech by the beamforming method. Firstly, the feedback canceller operates to cancel the feedback signal in the microphone signal, and then the noise canceller operates to reduce the noise in the residual signal. Also, to assure the stable convergence of binaural hearing aids in the training mode, the coefficients of the left hearing aid are firstly updated, then the coefficients of the right hearing aid are updated. In the normal mode, the feedback and the noise canceller are operated without updating coefficients except an unstable case. To verify performances of the proposed algorithm, we analyzed its convergence behavior and simulated for real speech. From the results of simulations, it was proved that we can advance 14.43dB SFR(speech-to-feedback ratio) on average in the feedback canceller, 10.19dB SNR(speech-to-noise ratio) improvement on average in the noise canceller, in the case of applying the proposed algorithm.

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

[1] D. K. Bustamante, T. L. Worrall, M. J. Williamson, "Measurement and adaptive suppression of acoustic feedback in hearing aids", Proc. ICASSP-89, pp.2017-2020, April 1989.

[2] J. M. Kates, "Feedback cancellation in hearing aids : results from a computer simulation", IEEE Trans. Signal Processing, Vol.39, No.3, pp.553-562, March 1991.
[CrossRef] [Web of Science Times Cited 64] [SCOPUS Times Cited 77]

[3] J. A. Maxwell, P. M. Zurek, "Reducing acoustic feedback in hearing aids", IEEE Trans., Speech Audio Processing, Vol.3, No.4, pp.304-313, July 1995.
[CrossRef] [Web of Science Times Cited 82] [SCOPUS Times Cited 108]

[4] J. E. Greenberg, P. M. Zurek, and M. Brantley, "Evaluation of feedback-reduction algorithms for hearing aids", J. Acoust. Soc. Amer., Vol.108, No.5, pp.2366-2376, November 2000.
[CrossRef] [PubMed] [Web of Science Times Cited 41] [SCOPUS Times Cited 50]

[5] S. Laugesen, K. V. Hansen, and J. Hellgren, "Acceptable delay in hearing aids and implications for feedback cancellation", J. Acoust. Soc. Amer., Vol.105, No.2, pp.1211-1212, 1999.

[6] J. Hellgren, U. Forssell, "Bias of feedback cancellation algorithm in hearing aids based on direct closed loop identification", IEEE Trans. Speech Audio Processing, Vol.9, No.8, pp.906-913, November 2001.
[CrossRef] [Web of Science Times Cited 47] [SCOPUS Times Cited 59]

[7] J. M. Kates, "Constrained adaptation for feedback cancellation in hearing aids", J. Acoust. Soc. Amer., Vol.106, No.2, pp.1010-1019, August 1999.
[CrossRef] [PubMed] [Web of Science Times Cited 56] [SCOPUS Times Cited 58]

[8] A. Spriet, I. Proudler, M. Moonen, and J. Wouters, "Adaptive feedback cancellation in hearing aids with linear prediction of the desired signal", IEEE Trans. Signal Process. Vol.53, No.10, pp.3749-3763, October 2005.
[CrossRef] [Web of Science Times Cited 106] [SCOPUS Times Cited 120]

[9] A. Farassopoulos, "Speech enhancement for hearing aids using adaptive beamformers", Proc. ICASSP-89, pp.1322-1325, May 1989.

[10] J. E. Greenberg, P. M. Zurek, "Evaluation of an adaptive beamforming method for hearing aids", J. Acoust. Soc. Amer., Vol.91, No.3, pp.1662-1676, March 1992.
[CrossRef] [PubMed] [Web of Science Times Cited 128] [SCOPUS Times Cited 158]

[11] J. V. Berghe, J. Wouters, "An adaptive noise canceller for hearing aids using two nearby microphones", J. Acoust. Soc. Amer., Vol.103, pp.3621-3626, June 1998.
[CrossRef] [PubMed] [Web of Science Times Cited 54] [SCOPUS Times Cited 67]

[12] A. Spriet, G. Rombouts, M. Moonen, J. Wouters, "Combined Feedback and noise suppression in hearing aids", IEEE Trans. Audio Speech Language Processing, Vol.15, No.6, pp.1777-1790, August 2007.
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 11]

[13] G. Rombouts, A. Spriet, M. Moonen, "Generalized sidelobe canceller based combined acoustic feedback and noise cancellation," ScienceDirect Signal Processing 88, pp.571-581, 2008.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 10]

[14] A. Lombard, K. Reindl, and W. Kellermann, "Combination of adaptive feedback cancellation and binaural adaptive filtering in hearing aids," EURASIP Journal on advances in signal processing, Vol.2009, 2009.
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 8]

[15] M. G. Siqueira, A. Alwan, "Steady-state analysis of continuous adaptation in acoustic feedback reduction system for hearing-aids", IEEE Trans. Speech Audio Processing, Vol.8, No.4, pp.443-453, July 2000.
[CrossRef] [Web of Science Times Cited 92] [SCOPUS Times Cited 118]

References Weight

Web of Science® Citations for all references: 689 TCR
SCOPUS® Citations for all references: 844 TCR

Web of Science® Average Citations per reference: 46 ACR
SCOPUS® Average Citations per reference: 56 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 2019-02-16 11:07 in 111 seconds.

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