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Subband Adaptive Filters

  • Paulo S. R. DinizEmail author
Chapter

Abstract

There are many applications where the required adaptive filter order is high, as for example, in acoustic echo cancellation where the unknown system (echo) model has a long impulse response, on the order of a few thousand samples [1, 2, 3, 4, 5, 6]. In such applications, the adaptive filtering algorithm entails a large number of computations. In addition, the high order of the adaptive filter affects the convergence speed.

References

  1. 1.
    K.A. Lee, W.S. Gan, S.M. Kuo, Subband Adaptive Filtering: Theory and Implementation (Wiley, Chichester, 2009)CrossRefGoogle Scholar
  2. 2.
    A. Gilloire, Experiments with sub-band acoustic echo cancellers for teleconferencing, in Proceedings of the IEEE International Conference on Acoustics, Speech, Signal Processing, Dallas, TX (1987), pp. 2141–2144Google Scholar
  3. 3.
    A. Gilloire, M. Vetterli, Adaptive filtering in subbands with critical sampling: analysis, experiments, and application to acoustic echo cancellation. IEEE Trans. Signal Process. 40, 1862–1875 (1992)CrossRefGoogle Scholar
  4. 4.
    W. Kellermann, Analysis and design of multirate systems for cancellation of acoustical echoes, in Proceedings of the IEEE International Conference on Acoustics, Speech, Signal Processing, New York, NY (1988), pp. 2570–2573Google Scholar
  5. 5.
    Y. Lu, J.M. Morris, Gabor expansion for adaptive echo cancellation. IEEE Signal Process. Mag. 16, 68–80 (1999)CrossRefGoogle Scholar
  6. 6.
    E. Hänsler, G.U. Schmidt, Hands-free telephones—joint control of echo cancellation and post filtering. Signal Process. 80, 2295–2305 (2000)CrossRefGoogle Scholar
  7. 7.
    P.L. De León, II, D.M. Etter, Experimental results with increased bandwidth analysis filters in oversampled, subband acoustic echo cancellers. IEEE Signal Process. Lett. 2, 1–3 (1995)CrossRefGoogle Scholar
  8. 8.
    E.A.B. da Silva, P.S.R. Diniz, Time-varying filters, in Encyclopedia of Electrical and Electronics Engineering, vol. 22, ed. by John G. Webster (Wiley, New York, 1999), pp. 249–274Google Scholar
  9. 9.
    P.P. Vaidyanathan, Multirate Systems and Filter Banks (Prentice-Hall, Englewood Cliffs, 1993)zbMATHGoogle Scholar
  10. 10.
    M. Vetterli, J. Kovačević Wavelets and Subband Coding (Prentice-Hall, Englewood Cliffs, 1995)Google Scholar
  11. 11.
    H. Bölcskei, F. Hlawatsch, Oversampled cosine modulated filter banks with perfect reconstruction. IEEE Trans. Signal Process. 45, 1057–1071 (1998)zbMATHGoogle Scholar
  12. 12.
    I.-S. Lin, S.K. Mitra, Overlapped block digital filtering. IEEE Trans. Circ. Syst. II: Analog Digit. Signal Process. 43, 586–596 (1996)Google Scholar
  13. 13.
    M.R. Petraglia, R.G. Alves, P.S.R. Diniz, New structures for adaptive filtering in subbands with critical sampling. IEEE Trans. Signal Process. 48, 3316–3327 (2000)MathSciNetCrossRefGoogle Scholar
  14. 14.
    M.R. Petraglia, R.G. Alves, P.S.R. Diniz, Convergence analysis of an oversampled subband adaptive filtering structure with local errors, in Proceedings of the IEEE International Symposium on Circuits and Systems, Geneve, Switzerland (2000), pp. I-563–I-566Google Scholar
  15. 15.
    M.R. Petraglia, R.G. Alves, P.S.R. Diniz, Convergence analysis of an oversampled subband adaptive filtering structure with global error, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, Turkey, Istanbul (2000), pp. 468–471Google Scholar
  16. 16.
    J.R. Treichler, S.L. Wood, M.G. Larimore, Convergence rate limitations in certain frequency-domain adaptive filters, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, Scotland (1989), pp. 960–963Google Scholar
  17. 17.
    G. Strang, Linear Algebra and Its Applications (Academic, New York, 1980)zbMATHGoogle Scholar
  18. 18.
    S.S. Pradhan, V.U. Reddy, A new approach to subband adaptive filtering. IEEE Trans. Signal Process. 47, 655–664 (1999)CrossRefGoogle Scholar
  19. 19.
    Y. Higa, H. Ochi, S. Kinjo, A subband adaptive filter with the statistically optimum analysis filter bank. IEEE Trans. Circ. Syst. II: Analog Digit. Signal Process. 45, 1150–1154 (1998)CrossRefGoogle Scholar
  20. 20.
    S.M. Kuo, D.R. Morgan, Active Noise Control Systems (Wiley, New York, 1996)Google Scholar
  21. 21.
    D.R. Morgan, M.J.C. Thi, A delayless subband adaptive filter architecture. IEEE Trans. Signal Process. 43, 1819–1830 (1995)CrossRefGoogle Scholar
  22. 22.
    R. Merched, P.S.R. Diniz, M.R. Petraglia, A delayless alias-free subband adaptive filter structure. IEEE Trans. Signal Process. 47, 1580–1591 (1999)CrossRefGoogle Scholar
  23. 23.
    R. Merched, P.S.R. Diniz, M.R. Petraglia, A delayless alias-free subband adaptive filter structure, in Proceedings of the 1997 IEEE International Symposium on Circuits and Systems, Hong-Kong (1997), pp. 2329–2332Google Scholar
  24. 24.
    N. Hirayama, H. Sakai, S. Miyagi, Delayless subband adaptive filtering using the Hadamard transform. IEEE Trans. Signal Process. 47, 1731–1734 (1999)CrossRefGoogle Scholar
  25. 25.
    S. Ohno, H. Sakai, On Delayless subband adaptive filtering by subband/fullband transforms. IEEE Signal Process. Lett. 6, 236–239 (1999)CrossRefGoogle Scholar
  26. 26.
    K. Nishikawa, H. Kiya, Conditions for convergence of a delayless subband adaptive filter and its efficient implementation. IEEE Trans. Signal Process. 46, 1158–1167 (1998)CrossRefGoogle Scholar
  27. 27.
    U. Iyer, M. Nayeri, H. Ochi, Polyphase based adaptive structure for adaptive filtering and tracking. IEEE Trans. Circ. Syst. II: Analog Digit. Signal Process. 43, 220–232 (1996)CrossRefGoogle Scholar
  28. 28.
    F.G.V. Resende Jr., P.S.R. Diniz, K. Tokuda, M. Kaneko, A. Nishihara, LMS-based algorithms with multi-band decomposition of the estimation error applied to system identification. IEICE Trans. Fund. Spec. Issue Digit. Signal Process. Jpn. E00-A, 1376–1383 (1997)Google Scholar
  29. 29.
    F.G.V. Resende Jr., P.S.R. Diniz, K. Tokuda, M. Kaneko, A. Nishihara, New adaptive algorithms based on multi-band decomposition of the error signal. IEEE Trans. Circ. Syst. II: Analog Digit. Signal Process. 45, 592–599 (1998)CrossRefGoogle Scholar
  30. 30.
    T.I. Laakso, V. Välimäki, M. Karjalainen, U.K. Laine, Splitting the unit delay. IEEE Signal Process. Mag. 13, 30–60 (1996)CrossRefGoogle Scholar
  31. 31.
    P.S.R. Diniz, E.A.B. da Silva, S.L. Netto, Digital Signal Processing: System Analysis and Design, 2nd edn. (Cambridge University Press, Cambridge, 2010)CrossRefGoogle Scholar
  32. 32.
    G.A. Clark, S.R. Parker, S.K. Mitra, A unified approach to time- and frequency-domain realization of FIR adaptive digital filters. IEEE Trans. Acoust. Speech Signal Process. (ASSP) 31, 1073–1083 (1983)CrossRefGoogle Scholar
  33. 33.
    P.C. Sommen, On the convergence properties of a partitioned block frequency domain adaptive filter (PBFDAF), in Proceedings of the European Signal Processing Conference, Spain, Barcelona (1990), pp. 201–203Google Scholar
  34. 34.
    J.-S. Soo, K. Pang, Multidelay block frequency domain adaptive filter. IEEE Trans. Acoust. Speech Signal Process. 38, 373–376 (1990)CrossRefGoogle Scholar
  35. 35.
    B. Fahang-Boroujeny, Analysis and efficient implementation of partitioned block LMS filters. IEEE Trans. Signal Process. 44, 2865–2868 (1996)CrossRefGoogle Scholar
  36. 36.
    E. Moulines, O.A. Amrane, Y. Grenier, The generalized multidelay adaptive filter: structure and convergence analysis. IEEE Trans. Signal Process. 43, 14–28 (1995)CrossRefGoogle Scholar
  37. 37.
    M. de Couville, P. Duhamel, Adaptive filtering in subbands using a weighted criterion. IEEE Trans. Signal Process. 46, 2359–2371 (1998)CrossRefGoogle Scholar
  38. 38.
    R. Merched, A.H. Sayed, An embedding approach to frequency-domain and subband adaptive filtering. IEEE Trans. Signal Process. 48, 2607–2619 (2000)CrossRefGoogle Scholar
  39. 39.
    K. Eneman, M. Moonen, Hybrid subband/frequency-domain adaptive filters. Signal Process. 81, 117–136 (2001)CrossRefGoogle Scholar
  40. 40.
    J.J. Shynk, Frequency-domain and multirate adaptive filtering. IEEE Signal Process. Mag. 9, 15–37 (1992)CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Universidade Federal do Rio de JaneiroNiteróiBrazil

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