Adaptive mixed-norm filtering algorithm based on SαSG noise model

被引:3
作者
Zha, Daifeng [1 ]
Qiu, Tianshuang [1 ]
机构
[1] Dalian Univ Technol, Sch Elect & Informat Engn, Dalian 116024, Peoples R China
关键词
adaptive filtering; alpha-stable distribution; second-order statistics; fractional lower-order statistics; impulsive noise; mixed norm; normalized step-size;
D O I
10.1016/j.dsp.2006.01.002
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The standard mixed-norm filtering algorithm exhibits slow convergence in stable distribution environment, requires a stationary operating environment, and employs a constant step-size that needs to be determined a priori. We proposed a new adaptive mixed moments filtering algorithm based on S alpha SG (symmetry alpha-stable Gaussian) noise model. The simulation experiments show that the proposed algorithm exhibits increased convergence rate and stability performance than the conventional mixed-norm algorithm. (C) 2005 Elsevier Inc. All rights reserved.
引用
收藏
页码:475 / 484
页数:10
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