• Journal of Internet Computing and Services
    ISSN 2287 - 1136(Online) / ISSN 1598 - 0170 (Print)
    http://jics.or.kr/

Recursive Estimation of Biased Zero-Error Probability for Adaptive Systems under Non-Gaussian Noise


Namyong Kim, Journal of Internet Computing and Services, Vol. 17, No. 1, pp. 1-6, Feb. 2016
10.7472/jksii.2016.17.1.01, Full Text:
Keywords: recursive probability, biased zero-error, biased Gaussian, impulsive, underwater communication

Abstract

The biased zero-error probability and its related algorithms require heavy computational burden related with some summation operations at each iteration time. In this paper, a recursive approach to the biased zero-error probability and related algorithms are proposed, and compared in the simulation environment of shallow water communication channels with ambient noise of biased Gaussian and impulsive noise. The proposed recursive method has significantly reduced computational burden regardless of sample size, contrast to the original MBZEP algorithm with computational complexity proportional to sample size. With this computational efficiency the proposed algorithm, compared with the block-processing method, shows the equivalent robustness to multipath fading, biased Gaussian and impulsive noise.


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Cite this article
[APA Style]
Namyong Kim (2016). Recursive Estimation of Biased Zero-Error Probability for Adaptive Systems under Non-Gaussian Noise. Journal of Internet Computing and Services, 17(1), 1-6. DOI: 10.7472/jksii.2016.17.1.01.

[IEEE Style]
N. Kim, "Recursive Estimation of Biased Zero-Error Probability for Adaptive Systems under Non-Gaussian Noise," Journal of Internet Computing and Services, vol. 17, no. 1, pp. 1-6, 2016. DOI: 10.7472/jksii.2016.17.1.01.

[ACM Style]
Namyong Kim. 2016. Recursive Estimation of Biased Zero-Error Probability for Adaptive Systems under Non-Gaussian Noise. Journal of Internet Computing and Services, 17, 1, (2016), 1-6. DOI: 10.7472/jksii.2016.17.1.01.