Abstract
In this paper, a normalized least mean square (NLMS) adaptive filtering algorithm based on the arctangent cost function that improves the robustness against impulsive interference is proposed. Owing to the excellent characteristics of the arctangent cost function, the adaptive update of the weight vector stops automatically in the presence of impulsive interference. Thus, this eliminates the likelihood of updating the weight vector based on wrong information resulting from the impulsive interference. When the priori error is small, the NLMS algorithm based on the arctangent cost function operates as the conventional NLMS algorithm. Simulation results show that the proposed algorithm can achieve better performance than the traditional NLMS algorithm, the normalized least logarithmic absolute difference algorithm and the normalized sign algorithm in system identification experiments that include impulsive interference and abrupt changes.
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Acknowledgments
This work was supported by Program for ChangJiang Scholars and Innovative Research Team in University (IRT1299), and the special fund of Chongqing key laboratory (CSTC), Chongqing University of Post and Telecommunications (Chongqing) Innovative Research Project Fund for Graduate Students (CYS14143), National Nature Science Foundation of China (61271259 and 61301123).
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Zeng, J., Lin, Y. & Shi, L. A Normalized Least Mean Square Algorithm Based on the Arctangent Cost Function Robust Against Impulsive Interference. Circuits Syst Signal Process 35, 3040–3047 (2016). https://doi.org/10.1007/s00034-015-0175-5
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DOI: https://doi.org/10.1007/s00034-015-0175-5