Skip to main content
SpringerLink
Log in

Robust Recursive Inverse Adaptive Algorithm in Impulsive Noise

  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

The recently proposed Recursive Inverse (RI) algorithm has shown a significant performance improvement compared to that of the Recursive Least Squares (RLS) algorithm, in various noise environments. However, both algorithms fail to converge in certain impulsive noise environments, especially if the Signal-to-Noise Ratio (SNR) is low. In this paper, a Robust RI algorithm is proposed. Analytical results show that robustness against impulsive noise is achieved by choosing the weights on the basis of the L 1 norms of the autocorrelation matrix and the cross-correlation vector. Simulation results confirm that the proposed algorithm provides an improved performance, with a reduction in computational complexity, compared to those of the RLS and the Robust RLS in white and correlated impulsive noise.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. M.S. Ahmad, O. Kukrer, A. Hocanin, An efficient Recursive Inverse adaptive filtering algorithm for channel equalization, in European Wireless Conference (EW 2010), Lucca, Italy (2010), pp. 88–92

    Chapter  Google Scholar 

  2. M.S. Ahmad, O. Kukrer, A. Hocanin, Recursive Inverse adaptive filtering algorithm. Digit. Signal Process. 21(4), 491–496 (2011)

    Article  Google Scholar 

  3. R.C. Bilcu, P. Kuosmanen, K. Egiazarian, A transform domain lms adaptive filter with variable step-size. IEEE Signal Process. Lett. 9(2), 51–53 (2002)

    Article  Google Scholar 

  4. M.Z.A. Bhotto, A. Antoniou, Robust recursive least-squares adaptive-filtering algorithm for impulsive-noise environments. IEEE Signal Process. Lett. 18(3), 185–188 (2011)

    Article  Google Scholar 

  5. H. Delic, A. Hocanin, Robust detection in DS/CDMA. IEEE Trans. Veh. Technol. 51(1), 155–170 (2002)

    Article  Google Scholar 

  6. P.S.R. Diniz, Adaptive filtering algorithms and practical implementation, 3rd edn. LLC (Springer, Berlin, 2008)

    MATH  Google Scholar 

  7. S. Haykin, Adaptive filter theory, 4th edn. (Prentice Hall, Upper Saddle River, 2002)

    Google Scholar 

  8. A.H. Sayed, Adaptive filters (Wiley, New York, 2008)

    Book  Google Scholar 

  9. B. Seyfe, S. Valaee, A new choice of penalty function for robust multiuser detection based on M-estimation. IEEE Trans. Commun. Theory 53, 224–227 (2005)

    Article  Google Scholar 

  10. Y. Zou, S.C. Chan, A robust quasi-Newton adaptive filtering algorithm for impulse noise suppression. IEEE Int. Symp. Circuits Syst. 2, 677–680 (2001)

    Google Scholar 

  11. Y. Zou, S.C. Chan, T.S. Ng, Robust M-estimate adaptive filtering. IEE Proc., Vis. Image Signal Process. 148(4), 289–294 (2001)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electrical & Electronic Engineering Department, Eastern Mediterranean University, via Mersin 10, Gazimagusa, Turkey

    Mohammad Shukri Ahmad, Osman Kukrer & Aykut Hocanin

Authors
  1. Mohammad Shukri Ahmad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Osman Kukrer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Aykut Hocanin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammad Shukri Ahmad.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ahmad, M.S., Kukrer, O. & Hocanin, A. Robust Recursive Inverse Adaptive Algorithm in Impulsive Noise. Circuits Syst Signal Process 31, 703–710 (2012). https://doi.org/10.1007/s00034-011-9341-6

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-011-9341-6

Keywords

Search

Navigation