Sign Subband Adaptive Filter with Selection of Number of Subbands

Jae Jin Jeong, Seung Hun Kim, Gyogwon Koo, Sang Woo Kim

2015

Abstract

The sign subband adaptive filter (SSAF) algorithm is introduced to reduce performance degradation of least-mean-square-type algorithms due to a correlated input signal or an impulsive noise environments. However, this algorithmh has huge computational complexity when the length of the unknown system is large. In this paper, we focus on reduce computational complexity of the conventional SSAF algorithm and propose an SSAF algorithm which selects number of subbands according to convergence state. The specific bands which contributes to decrease the mean-square deviation are used to update the adaptive filter. Thus, the proposed algorithm reduces the computational complexity compared to the conventional SSAF algorithm. The selection mehtod is derived by analysing the mean-square deviation. Through the computer simulation, simulation results are presented that demonstrate the fast convergence rate of the proposed algorithm and save the computational cost.

References

  1. Benesty, J., Rey, H., Rey Vega, L., and Tressens, S. (2006). A nonparametric vss nlms algorithm. Signal Processing Letters, IEEE, 13(10):581-584.
  2. Bershad, N., Eweda, E., and Bermudez, J. (2014). Stochastic analysis of the lms and nlms algorithms for cyclostationary white gaussian inputs.
  3. Kim, S.-E., Choi, Y.-S., Song, M.-K., and Song, W.-J. (2010). A subband adaptive filtering algorithm employing dynamic selection of subband filters. Signal Processing Letters, IEEE, 17(3):245-248.
  4. Lee, K. A. and Gan, W. S. (2004). Improving convergence of the nlms algorithm using constrained subband updates. Signal Processing Letters, IEEE, 11(9):736- 739.
  5. Lee, K.-A., Gan, W.-S., and Kuo, S. M. (2009). Subband adaptive filtering: theory and implementation. John Wiley & Sons.
  6. Mathews, V. J. and Cho, S. H. (1987). Improved convergence analysis of stochastic gradient adaptive filters using the sign algorithm. Acoustics, Speech and Signal Processing, IEEE Transactions on, 35(4):450- 454.
  7. Ni, J. and Li, F. (2010). Variable regularisation parameter sign subband adaptive filter. Electronics letters, 46(24):1605-1607.
  8. Rey Vega, L., Rey, H., Benesty, J., and Tressens, S. (2008). A new robust variable step-size nlms algorithm. Signal Processing, IEEE Transactions on, 56(5):1878- 1893.
  9. Sayed, A. H. (2003). Fundamentals of adaptive filtering. John Wiley & Sons.
  10. Shin, H.-C. and Sayed, A. H. (2004). Mean-square performance of a family of affine projection algorithms. Signal Processing, IEEE Transactions on, 52(1):90- 102.
  11. Yin, W. and Mehr, A. S. (2011). Stochastic analysis of the normalized subband adaptive filter algorithm. Circuits and Systems I: Regular Papers, IEEE Transactions on, 58(5):1020-1033.
  12. Yousef, N. R. and Sayed, A. H. (2001). A unified approach to the steady-state and tracking analyses of adaptive filters. Signal Processing, IEEE Transactions on, 49(2):314-324.
  13. Zou, Y., Chan, S., and Ng, T. (2000). A recursive least m-estimate (rlm) adaptive filter for robust filtering in impulse noise. Signal Processing Letters, IEEE, 7(11):324-326.
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Paper Citation


in Harvard Style

Jeong J., Kim S., Koo G. and Kim S. (2015). Sign Subband Adaptive Filter with Selection of Number of Subbands . In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-122-9, pages 407-411. DOI: 10.5220/0005537604070411


in Bibtex Style

@conference{icinco15,
author={Jae Jin Jeong and Seung Hun Kim and Gyogwon Koo and Sang Woo Kim},
title={Sign Subband Adaptive Filter with Selection of Number of Subbands},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2015},
pages={407-411},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005537604070411},
isbn={978-989-758-122-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Sign Subband Adaptive Filter with Selection of Number of Subbands
SN - 978-989-758-122-9
AU - Jeong J.
AU - Kim S.
AU - Koo G.
AU - Kim S.
PY - 2015
SP - 407
EP - 411
DO - 10.5220/0005537604070411