∈归一化符号回归最小平均四次方(NSRLMF)自适应算法

2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA) Pub Date : 2012-07-02 DOI:10.1109/ISSPA.2012.6310571

Mohammed Mujahid Ulla Faiz, A. Zerguine

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引用次数: 5

摘要

本文提出了一种新的算法，ϵ-normalized符号回归最小平均四分率(NSRLMF)算法来替代ϵ-normalized最小平均四分率(NLMF)算法。该算法显著降低了计算量。此外，该算法与ϵ-NLMF算法具有相似的收敛性。最后，模拟结果很好地证实了理论结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The ∈-normalized sign regressor least mean fourth (NSRLMF) adaptive algorithm

In this paper, a new algorithm, the ϵ-normalized sign regressor least mean fourth (NSRLMF) algorithm is presented as a substitute for the ϵ-normalized least mean fourth (NLMF) algorithm. This new algorithm reduces significantly the computational load. Moreover, the proposed algorithm has similar convergence properties as those of the ϵ-NLMF algorithm. Finally, simulations corroborate very well the theoretical findings.

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来源期刊

2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)

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