A new normalized subband adaptive filter under minimum error entropy criterion

被引：0
|
作者：
Lu Lu
Haiquan Zhao
Chenxi Chen
机构：
[1] Southwest Jiaotong University,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle, Ministry of Education, and School of Electrical Engineering
[2] University of Florida,Department of Mathematics
来源：
Signal, Image and Video Processing | 2016年 / 10卷
关键词：
Subband adaptive filtering; Convergence analysis; Minimum error entropy; Low signal-to-noise ratio (SNR);
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
引用
收藏
页码：1097 / 1103
页数：6
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