Skip to main content

Detection-Guided Fast Affine Projection Channel Estimator for Speech Applications


In various adaptive estimation applications, such as acoustic echo cancellation within teleconferencing systems, the input signal is a highly correlated speech. This, in general, leads to extremely slow convergence of the NLMS adaptive FIR estimator. As a result, for such applications, the affine projection algorithm (APA) or the low-complexity version, the fast affine projection (FAP) algorithm, is commonly employed instead of the NLMS algorithm. In such applications, the signal propagation channel may have a relatively low-dimensional impulse response structure, that is, the number m of active or significant taps within the (discrete-time modelled) channel impulse response is much less than the overall tap length n of the channel impulse response. For such cases, we investigate the inclusion of an active-parameter detection-guided concept within the fast affine projection FIR channel estimator. Simulation results indicate that the proposed detection-guided fast affine projection channel estimator has improved convergence speed and has lead to better steady-state performance than the standard fast affine projection channel estimator, especially in the important case of highly correlated speech input signals.



  1. 1.

    Ozeki K, Umeda T: An adaptive filtering algorithm using an orthogonal projection to an affine subspace and its properties. Electronics & Communications in Japan 1984,67(5):19-27.

    MathSciNet  Article  Google Scholar 

  2. 2.

    Gay SL, Tavathia S: The fast affine projection algorithm. Proceedings of the 20th International Conference on Acoustics, Speech, and Signal Processing (ICASSP '95), May 1995, Detroit, Mich, USA 5: 3023-3026.

    Google Scholar 

  3. 3.

    Casar-Corredera JR, Alcazar-Fernandez J: An acoustic echo canceller for teleconference systems. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '86), April 1986, Tokyo, Japan 11: 1317-1320.

    Article  Google Scholar 

  4. 4.

    Gilloire A, Zurcher J: Achieving the control of the acoustic echo in audio terminals. Proceedings of European Signal Processing Conference (EUSIPCO '88), September 1988, Grenoble, France 491-494.

    Google Scholar 

  5. 5.

    Makino S, Shimada S: Echo control in telecommunicaitons. Journal of the Acoustic Society of Japan 1990,11(6):309-316.

    Article  Google Scholar 

  6. 6.

    Homer J, Mareels I, Bitmead RR, Wahlberg B, Gustafsson A: LMS estimation via structural detection. IEEE Transactions on Signal Processing 1998,46(10):2651-2663. 10.1109/78.720368

    Article  Google Scholar 

  7. 7.

    Homer J: Detection guided NLMS estimation of sparsely parametrized channels. IEEE Transactions on Circuits and Systems II 2000,47(12):1437-1442. 10.1109/82.899637

    Article  Google Scholar 

  8. 8.

    Homer J, Mareels I, Hoang C: Enhanced detection-guided NLMS estimation of sparse FIR-modeled signal channels. IEEE Transactions on Circuits and Systems I 2006,53(8):1783-1791.

    Article  Google Scholar 

  9. 9.

    Haykin S: Adaptive Filter Theory, Prentice Hall Information and System Science Series. 3rd edition. Prentice-Hall, Upper Saddle River, NJ, USA; 1996.

    Google Scholar 

  10. 10.

    Bouchard M: Multichannel affine and fast affine projection algorithms for active noise control and acoustic equalization systems. IEEE Transactions on Speech and Audio Processing 2003,11(1):54-60. 10.1109/TSA.2002.805642

    Article  Google Scholar 

  11. 11.

    Sankaran SG, Beex AA: Convergence behavior of affine projection algorithms. IEEE Transactions on Signal Processing 2000,48(4):1086-1096. 10.1109/78.827542

    MathSciNet  Article  MATH  Google Scholar 

  12. 12.

    Rombouts G, Moonen M: A sparse block exact affine projection algorithm. IEEE Transactions on Speech and Audio Processing 2002,10(2):100-108. 10.1109/89.985547

    Article  Google Scholar 

  13. 13.

    Rombouts G, Moonen M: A fast exact frequency domain implementation of the exponentially windowed affine projection algorithm. Proceedings of IEEE Adaptive Systems for Signal Processing, Communications, and Control Symposium (AS-SPCC '00), October 2000, Lake Louise, Alta., Canada 342-346.

    Google Scholar 

  14. 14.

    Leadbetter MR, Lindgren G, Rootzen H: Extremes and Related Properties of Random Sequences and Processes. Springer, New York, NY, USA; 1982.

    Google Scholar 

  15. 15.

    Cramer H, Leadbetter MR: Stationary and Related Stochastic Srocesses: Sample Function Properties and Their Applications. John Wiley & Sons, New York, NY, USA; 1967.

    Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Yan Wu Jennifer.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Jennifer, Y.W., Homer, J., Rombouts, G. et al. Detection-Guided Fast Affine Projection Channel Estimator for Speech Applications. J AUDIO SPEECH MUSIC PROC. 2007, 071495 (2007).

Download citation


  • Channel Impulse Response
  • Channel Estimator
  • Adaptive Estimation
  • Speech Input
  • Engineer Acoustics