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http://dx.doi.org/10.7840/kics.2014.39A.5.237

Efficient Adaptive Algorithms Based on Zero-Error Probability Maximization  

Kim, Namyong (Division of Electronic, Information and Communication Eng. Kangwon National University)
Abstract
In this paper, a calculation-efficient method for weight update in the algorithm based on maximization of the zero-error probability (MZEP) is proposed. This method is to utilize the current slope value in calculation of the next slope value, replacing the block processing that requires a summation operation in a sample time period. The simulation results shows that the proposed method yields the same performance as the original MZEP algorithm while significantly reducing the computational time and complexity with no need for a buffer for error samples. Also the proposed algorithm produces faster convergence speed than the algorithm that is based on the error-entropy minimization.
Keywords
computational complexity; MEE; adaptive algorithm; zero-error probability;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 N. Kim, "Decision feedback equalizer based on maximization of zero-error probability," J. KICS, vol. 36, pp. 516-521, Aug. 2011.   DOI
2 D. Erdogmus and J. Principe, "An entropy minimization algorithm for supervised training of nonlinear systems," IEEE Trans. Signal Process., vol. 50, pp. 1780-1786, Jul. 2002.   DOI   ScienceOn
3 I. Santamaria, D. Erdogmus, and J. Principe, "Entropy minimization for supervised digital communications channel equalization," IEEE Trans. Signal Process., vol. 50, pp. 1184-1192, May 2002.   DOI   ScienceOn
4 N. Kim, K. Jung, and L. Yang, "Maximization of zero-error probability for adaptive channel equalization," JCN, vol. 12. pp. 459-465, Oct. 2010.
5 M. Girolami and C. He, "Probability density estimation from optimally condensed data samples," IEEE Trans. Pattern Anal. Machine Intelligence, vol. 25, pp. 1253-1264, Oct. 2003.   DOI   ScienceOn
6 J. Proakis, Digital Communications, 2nd edition, NY: McGraw-Hill, 1989.
7 J. Joung, "MSE-based power saving method for relay systems," J. KICS, vol. 34, pp. 562-567, Jul. 2009.   과학기술학회마을
8 E. Parzen, "On the estimation of a probability density function and the mode," Ann. Math. Stat., vol. 33, no. 3, pp. 1065-1076, Sept. 1962.   DOI   ScienceOn
9 J. Principe, D. Xu, and J. W. Fisher III, Information Theoretic Learning in: S. Haykin, Unsupervised Adaptive Filtering, NY: Wiley, pp. 265-319, 2000.