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Myriad Filter Computation with 2nd Order Approximation Polynomial

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Information Technologies in Biomedicine

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 69))

Abstract

The myriad filter is a robust filter which is very useful in suppressing impulsive noise. It belongs to the family of the robust m-filters and is controlled with one parameter only. The myriad filter is defined as a running window filter whose output is the sample myriad of elements in the window. In this paper, a fast and simple method of the myriad filter computation is presented. It performs the 2nd order polynomial fitting and the next x-coordinate of the parabola top is searched. The proposed method can operate on different types of impulsive noise, requires less computational time and is equally robust as the fixed point method or the branch-and-bound search method. The presented method is applied to process a chirp signal in the impulsive environment. The obtained results are compared to the fixed-point algorithm and the branch-and-bound searching method.

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References

  1. Barr, R.E., Chan, E.K.Y.: Design and implementation of digital filters for biomedical signal processing. J. Electrophysiol. Tech. (13), 73–93 (1986)

    Google Scholar 

  2. Chan, S., Zou, Y.: A Recursive least M-estimate algorithm for robust adaptive filtering in impulsive noise: fast algorithm and convergence performance analysis. IEEE Trans. on Signal Processing 52, 975–991 (2004)

    Article  MathSciNet  Google Scholar 

  3. Georgiou, P.G., Tsakalides, P., Kyriakakis, C.: Alpha-stable modeling of noise and robust time-delay estimation in the presence of impulsive noise. IEEE Trans. on Multimedia 1, 291–301 (1999)

    Article  Google Scholar 

  4. Gonzalez, J.G., Arce, G.R.: Optimality of the myriad filter in practical impulsive-noise environments. IEEE Trans. on Signal Processing 49, 438–441 (2001)

    Article  Google Scholar 

  5. Gonzalez, J.G., Griffith, D.W., Arce, G.R.: Matched myriad filtering for robust communications. In: Proc. Conf. Inform. Sci. Syst., Princeton, NY, USA (March 1996)

    Google Scholar 

  6. Gonzalez, J.G., Lau, D.L., Arce, G.R.: Towards a general theory of robust nonlinear filtering: selection filters. In: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 1997), Munich, Germany, April 21-24, pp. 3837–3840 (1997)

    Google Scholar 

  7. Gonzalez, J.G., Arce, G.R.: Statistically-Efficient Filtering in Impulsive Environments: Weighted Myriad Filters. EURASIP Journal on Applied Signal Processing 1, 4–20 (2002)

    Google Scholar 

  8. Gonzalez, J.G., Paredes, J.L., Arce, G.R.: Zero-order statistics: a mathematical framework for the processing and characterization of very impulsive signals. IEEE Trans. on Signal Processing 54, 3839–3851 (2006)

    Article  Google Scholar 

  9. Hong, X., Chen, S.: M-estimator and D-optimality model construction using orthogonal forward regression. IEEE Trans. on Systems Man and Cybernetics 35, 1–7 (2005)

    Google Scholar 

  10. Li, S.Z.: Robustizing robust M-estimation using deterministic annealing. Pattern Recognition 29, 159–166 (1996)

    Article  Google Scholar 

  11. Hamza, B.A., Krim, H.: Image denoising: a nonlinear robust statistical approach. IEEE Trans. on Signal Processing 49, 3045–3054 (2001)

    Article  Google Scholar 

  12. Hu, X., Nenov, V.: A single-lead ECG enhancement algorithm using a regularized data-driven filter. IEEE Trans. on Biomedical Eng. 2, 347–351 (2006)

    Article  Google Scholar 

  13. Kalluri, S., Arce, G.R.: Adaptive weighted myriad filter algorithms for robust signal processing in a-stable noise environments. IEEE Trans. on Signal Processing 46, 322–334 (1998)

    Article  Google Scholar 

  14. Kalluri, S., Arce, G.R.: Fast algorithms for weighted myriad computation by fixed point search. IEEE Trans. on Signal Processing 48, 159–171 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  15. Kalluri, S., Arce, G.R.: Robust frequency-selective filtering using weighted myriad filters admitting real-valued weights. IEEE Trans. on Signal Processing 49, 2721–2733 (2001)

    Article  Google Scholar 

  16. Shao, M., Nikias, C.L.: Signal processing with fractional lower order moments: stable processes and their applications. Proc. of the IEEE 81, 986–1009 (1993)

    Article  Google Scholar 

  17. Pander, T.: An application of a weighted myriad filter to suppression an impulsive type of noise in biomedical signals. TASK Quartarly 2, 199–216 (2004)

    Google Scholar 

  18. Kim, K., Shevlyakov, G.: Why Gaussianity? IEEE Signal Processing Magazine 3, 102–113 (2008)

    Google Scholar 

  19. Aysal, T.C., Barner, K.E.: Meridian Filtering for Robust Signal Processing. IEEE Transactions on Signal Processing 55, 3939–3962 (2007)

    Google Scholar 

  20. Núñez, R.C., Gonzalez, J.G., Arce, G.R.: Fast and Accurate Computation of the Myriad Filter via Branch-and-Bound Search. IEEE Transactions on Signal Processing 56, 3340–3346 (2008)

    Article  MathSciNet  Google Scholar 

  21. Łȩski, J.: Robust Weighted Averaging. IEEE Transactions on Biomedical Engineering 49, 796–804 (2002)

    Article  Google Scholar 

  22. Surender, V.P., Ganguli, R.: Adaptive Myriad Filter for Improved Gas Turbine Condition Monitoring Using Transient Data. Journal of Eng. for Gas Turbines and Power 127, 329–339 (2005)

    Article  Google Scholar 

  23. Lim, H.S., Chuah, T.C., Chuah, H.T.: On the Optimal Alpha-k Curve of the Sample Myriad. IEEE Signal Processing Letters 14, 545–548 (2007)

    Article  Google Scholar 

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Pander, T. (2010). Myriad Filter Computation with 2nd Order Approximation Polynomial. In: Piȩtka, E., Kawa, J. (eds) Information Technologies in Biomedicine. Advances in Intelligent and Soft Computing, vol 69. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13105-9_25

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  • DOI: https://doi.org/10.1007/978-3-642-13105-9_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13104-2

  • Online ISBN: 978-3-642-13105-9

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