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Subband and MSF Performance Comparison for AEC

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Signal Processing and Information Technology (SPIT 2011)

Abstract

We have designed and simulated two techniques for acoustic echo cancellation. These systems are based upon a least-mean-square (LMS) adaptive algorithm and uses multi sub and sub band technique. A comparative study of both methods has been carried out.

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References

  1. Bershad, N.J., Bermudez, J.C.M., Tourneret, J.-Y.: An affine combination of two LMS adaptive filters —Transient mean-square analysis. IEEE Trans. Signal Process. 56(5), 1853–1864 (2008)

    Article  MathSciNet  Google Scholar 

  2. Petraglia, M.R., Batalheiro, P.B.: Non uniform sub band adaptive filtering with critical sampling. IEEE Trans. Signal Process. 56(2), 565–575 (2008)

    Article  MathSciNet  Google Scholar 

  3. Sayed, A.H.: Adaptive Filters. Wiley, New York (2008)

    Book  Google Scholar 

  4. Ding, H.: Fast affine projection adaptation algorithms with stable and robust symmetric linear system solvers. IEEE Trans. Signal Process. 55(5), 1730–1740 (2007)

    Article  MathSciNet  Google Scholar 

  5. Ni, J., Li, F.: A variable regularization matrix normalized sub band adaptive filter. IEEE Signal Process. 16(2), 105–108 (2009)

    Article  Google Scholar 

  6. Lee, K.A., Gan, W.S., Kuo, S.M.: Sub band Adaptive Filtering: Theory and Implementation. Wiley, Hoboken (2009)

    Book  Google Scholar 

  7. Lee, K.A., Gan, W.S.: Inherent décor-relating and leastperturbation properties of the normalized sub band adaptive filter. IEEE Trans. Signal Process. 54(11), 4475–4480 (2006)

    Article  Google Scholar 

  8. Arenas-Garcia, J., Figueira-Vidal, A.R., Sayed, A.H.: Mean-square performance of a convex combination of two adaptive filters. IEEE Trans. Signal Process. 54(3), 1078–1090 (2006)

    Article  Google Scholar 

  9. Sondhi, M.M.: The history of echo cancellation. IEEE Signal Process. Mag. 23(5), 95–98 (2008)

    Article  Google Scholar 

  10. Kao, C.C.: Design of echo cancellation and noise elimination for speech enhancement. IEEE Trans. Consumer Electronics 49(4), 1468–1473 (2003)

    Article  Google Scholar 

  11. Courville, M.D., Duhamel, P.: Adaptive filtering in sub bands using a weighted criterion. IEEE Trans. Signal Process. 46(9), 2359–2371 (1998)

    Article  Google Scholar 

  12. Pradhan, S.S., Reddy, V.U.: A new approach to sub band adaptive filtering. IEEE Trans. Signal Process. 47(3), 655–664 (1999)

    Article  Google Scholar 

  13. Lee, K.A., Gan, W.S.: Improving convergence of the NLMS algorithm using constrained sub band updates. IEEE Signal Process. Lett. 11(9), 736–739 (2004)

    Article  Google Scholar 

  14. Azpicueta-Ruiz, L.A., Figueiras-Vidal, A.R., Arenas-García, J.: A.:Acoustic echo cancellation in frequency domain using combinations of filters. In: 19th Int. Congress on Acoustics (ICA), Madrid (September 2007)

    Google Scholar 

  15. Ohno, S., Sakai, H.: Convergence Behavior of the LMS algorithm in sub band adaptive filtering. Signal Processing 81, 1053–1059 (2001) ISBN 0165-1684

    Article  MATH  Google Scholar 

  16. Brennan, R., Schneiderm: A flexible filter bank Structure for extensive signal manipulation in digital Hearing aids. In: Proc. IEEE Int. Symp. Circuits and Systems, pp. 569–572 (1998)

    Google Scholar 

  17. Chao, J., Kawabe, S., Tsujii, S.: A new IIR adaptive echo canceller. IEEE Journal on Selc. Areas in Corn. 12, 1530–1539 (1994)

    Article  Google Scholar 

  18. Widrow, B., Stearns, S.: Adaptive Signal Processing. Prentice-Hall, Englewood Cliffs (1985)

    MATH  Google Scholar 

  19. Kellermann, W.: Analysis and design of multirate systems for cancellation of acoustical echoes. In: Proc. Int. Conf. Acoust., Speech, Signal Proc., New York, pp. 2570–2573 (1988)

    Google Scholar 

  20. Gilloire, A., Vetterli, M.: Adaptive filtering in sub-bands. In: Proc. Int. Conf. Acoustic. Speech, Signal Proc., New York, NY (April 1988)

    Google Scholar 

  21. Irina, D.: Marina.:Subabd Adaptive Filtering, pp. 810–813. IEEE (2009)

    Google Scholar 

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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Sahu, O.P., Dhull, S.K., Arya, S.K. (2012). Subband and MSF Performance Comparison for AEC. In: Das, V.V., Ariwa, E., Rahayu, S.B. (eds) Signal Processing and Information Technology. SPIT 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32573-1_40

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  • DOI: https://doi.org/10.1007/978-3-642-32573-1_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32572-4

  • Online ISBN: 978-3-642-32573-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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