Login | Register

Mean square performance evaluation in frequency domain for an improved adaptive feedback cancellation in hearing aids


Mean square performance evaluation in frequency domain for an improved adaptive feedback cancellation in hearing aids

Kar, Asutosh, Anand, Ankita, Østergaard, Jan, Jensen, Søren Holdt and Swamy, M. N. S. ORCID: https://orcid.org/0000-0002-3989-5476 (2019) Mean square performance evaluation in frequency domain for an improved adaptive feedback cancellation in hearing aids. Signal Processing, 157 . pp. 45-61. ISSN 01651684

Text (application/pdf)
Mean-Square-Performance-Evaluation-in-Frequency-Domain-for-an-_2018_Signal-P.pdf - Accepted Version
Restricted to Repository staff only until 9 November 2020.
Available under License Spectrum Terms of Access.

Official URL: http://dx.doi.org/10.1016/j.sigpro.2018.11.003


We consider an adaptive linear prediction based feedback canceller for hearing aids that exploits two (an external and a shaped) noise signals for a bias-less adaptive estimation. In particular, the bias in the estimate of the feedback path is reduced by synthesizing the high-frequency spectrum of the reinforced signal using a shaped noise signal. Moreover, a second shaped (probe) noise signal is used to reduce the closed-loop signal correlation between the acoustic input and the loudspeaker signal at low frequencies. A power-transfer-function analysis of the system is provided, from which the effect of the system parameters and adaptive algorithms [normalized least mean square (NLMS) and recursive least square (RLS)] on the rate of convergence, the steady-state behaviour and the stability of the feedback canceller is explicitly found. The derived expressions are verified through computer simulations. It is found that, as compared to feedback canceller without probe noise, the cost of achieving an unbiased estimate of the feedback path using the feedback canceller with probe noise is a higher steady-state misadjustment for the RLS algorithm, whereas a slower convergence and a higher tracking error for the NLMS algorithm.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Article
Authors:Kar, Asutosh and Anand, Ankita and Østergaard, Jan and Jensen, Søren Holdt and Swamy, M. N. S.
Journal or Publication:Signal Processing
Date:8 April 2019
  • European Union’s Seventh Framework Programme (FP7/2007-2013) under the Grant agreement number ITN-GA-2012-316969.
Digital Object Identifier (DOI):10.1016/j.sigpro.2018.11.003
Keywords:Adaptive filters; Feedback cancellation; Probe noise; Hearing-aid; Band-limited LPC vocoder; Convergence rate; Power transfer function
ID Code:985241
Deposited By: MONIQUE LANE
Deposited On:08 Apr 2019 18:25
Last Modified:08 Apr 2019 18:25
Additional Information:The authors would like to thank Prof. Toon van Waterschoot (KU Leuven, Belgium) for his valuable suggestions throughout this work.


S.F. Lybarger Acoustic feedback control Vanderbilt Hear.-Aid Rep. (1982), pp. 87-90

J.M. Kates, Adaptive Feedback Cancellation in Hearing Aids, Springer, Berlin, Heidelberg, pp. 23–57.

B. Rafaely, M. Roccasalva-Firenze Control of feedback in hearing aids-a robust filter design approach IEEE Trans. Speech Audio Process., 8 (6) (2000), pp. 754-756

J. Hellgren, T. Lunner, S. Arlinger System identification of feedback in hearing aids J. Acoust. Soc. Am., 105 (6) (1999), pp. 3481-3496

A. Spriet, S. Doclo, M. Moonen, J. Wouters Feedback control in hearing aids
Springer Handbook of Speech Processing, Springer (2008), pp. 979-1000

G. Ma, F. Gran, F. Jacobsen, F.T. Agerkvist Adaptive feedback cancellation with band-limited {LPC} vocoder in digital hearing aids IEEE Trans. Audio Speech Lang. Process., 19 (4) (2011), pp. 677-687

A. Anand, A. Kar, M.N.S. Swamy Design and analysis of a {BLPC} vocoder-based adaptive feedback cancellation with probe noise Appl. Acoust., 115 (2017), pp. 196-208

M. Guo Analysis, Design, and Evaluation of Acoustic Feedback Cancellation Systems for Hearing Aids, Ph.D. thesis, PhD dissertation, Department of Electronic Systems, Aalborg University (2012)

H. Dillon, Hearing Aids, Boomerang press, Sydney, Australia.

B. Moore, An Introduction to the Psychology of Hearing, Brill.

S.S. Haykin Adaptive Filter Theory Prentice-Hall information and system sciences series, Prentice Hall (1991)
URL https://books.google.co.in/books?id=E5hTAAAAMAAJ.

M. Guo, T.B. Elmedyb, S.H. Jensen, J. Jensen Analysis of acoustic feedback/echo cancellation in multiple-microphone and single-loudspeaker systems using a power transfer function method
Signal Process. IEEE Trans., 59 (12) (2011), pp. 5774-5788

M. Guo, S.H. Jensen, J. Jensen Novel acoustic feedback cancellation approaches in hearing aid applications using probe noise and probe noise enhancement IEEE Trans. Audio Speech Lang. Process., 20 (9) (2012), pp. 2549-2563

S. Gunnarsson, L. Ljung Frequency domain tracking characteristics of adaptive algorithms IEEE Trans. Acoust., 37 (7) (1989), pp. 1072-1089

V. Krishnan Probability and Random Processes Wiley Survival Guides in Engineering and Science, Wiley (2006)
URL https://books.google.co.in/books?id=ckklgif1M68C.

H. Nyquist Regeneration theory Bell Syst. Tech. J., 11 (1) (1932), pp. 126-147

S. Gunnarsson On the quality of recursively identified fir models
IEEE Trans. Signal Process., 40 (3) (1992), pp. 679-682

C.R.C. Nakagawa Control of Feedback for Assistive Listening Devices, PhD dissertation, Ph.D. thesis, School of Electrical and Computer Engineering, Curtin University (2014)

T. Painter, A. Spanias Perceptual coding of digital audio Proc. IEEE, 88 (4) (2000), pp. 451-515

T. van Waterschoot, M. Moonen Fifty years of acoustic feedback control: state of the art and future challenges Proc. IEEE, 99 (2) (2011), pp. 288-327

A. Spriet, I. Proudler, M. Moonen, J. Wouters Adaptive feedback cancellation in hearing aids with linear prediction of the desired signal IEEE Trans. Signal Process., 53 (10) (2005), pp. 3749-3763

J.D. Johnston Transform coding of audio signals using perceptual noise criteria IEEE J. Sel. Areas Commun., 6 (2) (1988), pp. 314-323,

P. Loizou Speech Enhancement: Theory and Practice
(Second ed.), Taylor & Francis (2013) URL https://books.google.co.in/books?id=ntXLfZkuGTwC.

H.J. Kushner Approximation and Weak Convergence Methods for Random Processes, With Applications to Stochastic Systems Theory
Cambridge, Mass. : MIT Press (1984)

R.M. Gray, et al. Toeplitz and circulant matrices: a review
Found. Trends Commun.Inf. Theory, 2 (3) (2006), pp. 155-239
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Research related to the current document (at the CORE website)
- Research related to the current document (at the CORE website)
Back to top Back to top