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A new normalized subband adaptive filter under minimum error entropy criterion

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Abstract

A new normalized subband adaptive filter based on the minimum error entropy criterion (MEE-NSAF) is proposed for identifying a highly noisy system. The MEE-NSAF utilizes a kernel function and a number of past errors in adaptation, whereas the classical NSAF relies only on the current error signal. Moreover, the stability of the MEE-NSAF is analyzed. To further improve the performance of the MEE-NSAF under the sparse impulse responses, an improved proportionate MEE-NSAF (MEE-IPNSAF) algorithm is proposed. Simulation results show that the proposed algorithms can achieve improved performance as compared with the conventional NSAF when noise gets severe.

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Acknowledgments

This work was supported in part by National Natural Science Foundation of China (Grants: 61271340, 61571374, 61433011, U1234203) and the Fundamental Research Funds for the Central Universities (Grant: SWJTU12CX026).

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Authors and Affiliations

  1. Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle, Ministry of Education, and School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China

    Lu Lu & Haiquan Zhao

  2. Department of Mathematics, University of Florida, Gainesville, FL, USA

    Chenxi Chen

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  1. Lu Lu
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  2. Haiquan Zhao
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  3. Chenxi Chen
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Correspondence to Haiquan Zhao.

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Lu, L., Zhao, H. & Chen, C. A new normalized subband adaptive filter under minimum error entropy criterion. SIViP 10, 1097–1103 (2016). https://doi.org/10.1007/s11760-016-0864-y

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  • DOI: https://doi.org/10.1007/s11760-016-0864-y

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