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임펄스성 잡음의 유무를 결정하는 Kolmogorov-Smirnov 검증의 수치적 접근의 효율성

Numerical Approach with Kolmogorov-Smirnov Test for Detection of Impulsive Noise

  • Oh, Hyungkook (Hanyang University Department of Electronics & Communication Engineering) ;
  • Nam, Haewoon (Hanyang University Department of Electronics & Communication Engineering)
  • 투고 : 2014.05.24
  • 심사 : 2014.08.19
  • 발행 : 2014.09.30

초록

본 논문에서 임펄스성 잡음의 유무를 검증하는 알고리즘을 제안한다. 본 알고리즘을 제안하는 이유는 기존의 Kolmogorov-Smirnov 검증의 단점으로 낮은 분류 성공률 및 높은 복잡도가 있기 때문이다. 이는 이론적으로 문제가 없으나 실제로 구현함에 있어 많은 문제를 야기한다. 먼저 기존의 검증 방법을 설명 후 제안하는 알고리즘을 설명한다. 이 알고리즘은 기존의 Kolmogorov-Smirnov 검증 방법의 이론적 배경으로부터 제안된다. 알고리즘의 효율성을 증명하기 위해 임펄스성 잡음의 샘플을 이용하여 실험 후, 검증 실패 확률을 조사한다. 검증 실패 확률에 기반한 실험 결과는 제안한 알고리즘의 효율성을 증명한다.

This paper proposes an efficient algorithm based on Kolmogorov-Smirnov test to determine the presence of impulsive noise in the given environment. Kolmogorov-Smirnov and Chi-Square tests are known in the literature to serve as a goodness-of-fit test especially for a testing for normality of the distribution. But these algorithms are difficult to implement in practice due to high complexity. The proposed algorithm gives a significant reduction of the computational complexity while decreasing the error probability of hypothesis test, which is shown in the simulation results. Also, it is worth noting that the proposed algorithm is not dependent on the noise environment.

키워드

참고문헌

  1. D. Middleton, "Statistical-physical models of electromagnetic interference," IEEE Trans. Electromagn. Compat., vol. EMC-19, no. 3, pp. 106-127, Aug. 1977. https://doi.org/10.1109/TEMC.1977.303527
  2. A. D. Spaulding and D. Middleton, "Optimum reception in an impulsive interference environment-part I: Coherent detection," IEEE Trans. Commun., vol. COM-25, no. 9, pp. 910-923, Sept. 1977.
  3. D. Middleton, "Non-gaussian noise models in signal processing for telecommunications: New methods and results for class a and Class b noise models," IEEE Trans. Inf. Theory, vol. 45, no. 4, pp. 1129-1149, May 1999. https://doi.org/10.1109/18.761256
  4. K. Gulati, B. L. Evans, J. G. Andrews, and K. R. Tinsley, "Statistics of co-channel interference in a field of poisson and poisson-poisson clustered interferers," IEEE Trans. Signal Process., vol. 58, no. 12, pp. 6027-6222, Dec. 2010.
  5. T. S. Saleh, I. Marshland, and M. El-Tanany, "Suboptimal detectors for alpha-stable noise: Simplifying design and improving performance," IEEE Trans. Commun., vol. 60, no. 10, pp. 2982-2989, Oct. 2012. https://doi.org/10.1109/TCOMM.2012.071812.100789
  6. S. M. Zabin and H. V. Poor, "Parameter estimation for middleton class a interference processes," IEEE Trans. Commun., vol. 37, no. 10, pp. 1042-1051, Oct. 1989. https://doi.org/10.1109/26.41159
  7. S. M. Zabin and H. V. Poor, "Efficient estimation of class a noise parameters via the EM algorithm," IEEE Trans. Inf. Theory, vol. 37, no. 1, pp. 60-72, Jan. 1991. https://doi.org/10.1109/18.61127
  8. J. Friedman, H. Messer, and J. Cardoso, "Robust parameter estimation of a deterministic signal in impulsive noise," IEEE Trans. Signal Process., vol. 48, no. 4, pp. 935-942, Apr. 2000. https://doi.org/10.1109/78.827528
  9. K. S. Vastola, "Threshold detection in narrow-band non-gaussian noise," IEEE Trans. Commun., vol. COM-32, no. 2, pp. 134-138, Feb. 1984.
  10. D. J. Gibbsons, Nonparametric Methods for Quantitative Analysis, 3rd Ed., Amor Sciences, 1996.
  11. W. J. Conover, Practical Nonparametric Statistics, 3rd Ed., Wiley, 1999.
  12. J. H. Drew, A. G. Glen, and L. M. Leemis, "Computing the cumulative distribution function of the kolmogorov smirnov statistic," Computational Statics & Data Analysis, vol. 34, no. 1, pp. 1-15, Jul. 2000. https://doi.org/10.1016/S0167-9473(99)00069-9
  13. M. Chiani and D. Dardari, "Improved exponential bounds and approximation for the Q-function with application to average error probability," in Proc. IEEE GLOBECOM, pp. 1399-1402, Taipei, Taiwan, Nov. 2002.