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A Frequency Domain LMS Algorithm with Dynamic Selection of Frequency Bins

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Abstract

Frequency-domain (FD) adaptive filter algorithms are able to achieve a low computational complexity by using the overlap-and-save implementation means compared to time-domain (TD) ones. In this article, we propose a new FD least-mean-square (FD-LMS) algorithm which dynamically selects frequency bins in order to reduce the computational complexity and maintain the convergence performance of the conventional FD-LMS. The optimal selection of frequency bins is derived by the largest decrease between the successive FD mean square deviations (MSDs) at every data block. Simulation results show that the proposed algorithm provides a low steady-state normalized MSD (NMSD) and similar convergence rate compared to the conventional FD-LMS algorithm. In addition, it gains a low computational complexity.

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References

  1. M.S.E. Abadi, J.H. Husoy, Selective partial update and set-membership subband adaptive filters. Signal Process. 88, 2463–2471 (2008)

    Article  MATH  Google Scholar 

  2. M.S.E. Abadi, V. Mehrdad, Family of affine projection adaptive filters with selective partial updates and selective regressors. IET Signal. Process. 4(5), 567–575 (2010)

    Article  MathSciNet  Google Scholar 

  3. J. Benesty, H. Rey, L.R. Vega, S. Tressens, A nonparametric VSS NLMS algorithm. IEEE Signal Process. Lett. 13(10), 581–584 (2006)

    Article  Google Scholar 

  4. B.F. Boroujeny, K.S. Chan, Analysis of the frequency-domain block LMS algorithm. IEEE Trans. Signal Process. 48(8), 173–184 (2000)

    Google Scholar 

  5. C.F.N. Cowan, P.M. Grant, Adaptive Filters, 4th edn. (Prentice-Hall, Englewood Cliffs, 1985)

    MATH  Google Scholar 

  6. K. Dogancay, O. Tannkulu, Adaptive filtering algorithms with selective partial updates. IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process. 48(8), 726–729 (2001)

    Article  Google Scholar 

  7. S.C. Douglas, Analysis and implementation of the max-NLMS adaptive filter, in Proc. 29th Asilomar Conf. Signal, Syst. Comput. (1995), pp. 659–663

    Google Scholar 

  8. L. Guo, Y.F. Huang, Frequency-domain set-membership filtering and its applications. IEEE Trans. Signal Process. 55(4), 1326–1338 (2007)

    Article  MathSciNet  Google Scholar 

  9. S. Haykin, Adaptive Filter Theory, 4th edn. (Prentice-Hall, Upper Saddle River, 2002)

    Google Scholar 

  10. Y. Huang, J. Benesty, Audio Signal Processing for Next Generation Multimedia Communication Systems (Kluwer, Norwell, 2004)

    Book  Google Scholar 

  11. K.Y. Hwang, W.J. Song, An affine projection adaptive filtering algorithm with selective regressors. IEEE Trans. Circuits Syst. II, Express Briefs 54(1), 43–46 (2007)

    Article  Google Scholar 

  12. A.W.H. Khong, P.A. Naylor, Selective-tap adaptive filtering with performance analysis for identification of time-varying systems. IEEE Trans. Audio Speech Lang. Process. 15(5), 1681–1695 (2007)

    Article  Google Scholar 

  13. A.W.H. Khong, X. Lin, M. Doroslovacki, P.A. Naylor, Frequency domain selective tap adaptive algorithms for sparse system identification, in Proc. IEEE Int Conf. Acoust. Speech Signal Process. (ICASSP) (2008), pp. 229–232

    Google Scholar 

  14. S.J. Kong, K.Y. Hwang, W.J. Song, An affine projection algorithm with dynamic selection of input vectors. IEEE Signal Process. Lett. 14(8), 529–532 (2007)

    Article  Google Scholar 

  15. J.C. Lee, C.K. Un, Performance analysis of frequency-domain block LMS adaptive digital filters. IEEE Trans. Signal Process. 36(2), 173–184 (1989)

    MathSciNet  Google Scholar 

  16. X. Lin, A.W.H. Khong, M. Doroslovacki, P.A. Naylor, Frequency-domain adaptive algorithm for networks echo cancellation in VoIP. EURASIP J. Audio Speech Music Process. 2008, 1–9 (2008)

    Article  Google Scholar 

  17. J. Ni, F. Li, A variable regularization matrix normalized subband adaptive filter. IEEE Signal Process. Lett. 16(2), 125–128 (2009)

    Article  Google Scholar 

  18. B.H. Nitsch, A frequency-selective stepfactor control for an adaptive filter algorithm working in the frequency domain. Signal Process. 80, 1722–1745 (1992)

    Google Scholar 

  19. K. Ozeki, T. Umeda, An adaptive filtering using an orthogonal projection to an affine subspace and its properties. Electron. Commun. Jpn. 67-A(5), 19–27 (1984)

    MathSciNet  Google Scholar 

  20. I. Pitas, Fast algorithm for running ordering and max/min calculation. IEEE Trans. Circuits Syst. 36(6), 795–804 (1989)

    Article  Google Scholar 

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

    Book  Google Scholar 

  22. K. Shi, X. Ma, A frequency domain step-size control method for LMS algorithm. IEEE Signal Process. Lett. 17(2), 125–128 (2010)

    Article  Google Scholar 

  23. J.J. Shynk, Frequency-domain and multirate adaptive filtering. IEEE Signal Process. Mag. 9(1), 14–37 (1992)

    Article  Google Scholar 

  24. J. Sien, K.K. Pang, Multidelay block frequency domain adaptive filter. IEEE Trans. Acoust. Speech Signal Process. 38(2), 373–376 (1990)

    Article  Google Scholar 

  25. J.M. Valin, On adjusting the learning rate in frequency domain echo cancellation with double-talk. IEEE Trans. Audio Speech Lang. Process. 15(3), 1030–1034 (2007)

    Article  Google Scholar 

  26. S. Werner, P.S.R. Diniz, Set-membership affine projection algorithm. IEEE Signal Process. Lett. 8(8), 231–235 (2001)

    Article  Google Scholar 

  27. S. Werner, P.S.R. Diniz, J.E.W. Moreira, Set-membership affine projection algorithm with variable data-reuse factor, in Proc. 2006 IEEE Int. Synp. Circuits and Syst (2006), pp. 261–264

    Google Scholar 

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

    MATH  Google Scholar 

  29. Y. Zhou, X. Li, A variable step-size for frequency-domain acoustic echo cancellation, in Proc. IEEE Workshop Appl. Signal Process. Audio Acoust (2007), pp. 303–306

    Chapter  Google Scholar 

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Acknowledgements

The authors would like to express their thanks to the supports of the 2009 Guangdong–Hongkong major breakthrough in key fields project (200920523300 005), Sichuan key technology support program (2010GZ0149), and basic research funding from special operations (ZYGX2010J020).

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Authors and Affiliations

  1. School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, China

    Chang Liu, Zishu He & Wei Xia

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  1. Chang Liu
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  2. Zishu He
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  3. Wei Xia
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Correspondence to Chang Liu.

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Liu, C., He, Z. & Xia, W. A Frequency Domain LMS Algorithm with Dynamic Selection of Frequency Bins. Circuits Syst Signal Process 31, 2103–2118 (2012). https://doi.org/10.1007/s00034-012-9422-1

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