Variable-Step-Size Efficient Proportionate Affine Projection Sign Algorithms

被引:0
|
作者
Li, Guoliang [1 ,2 ]
Zhou, Xingli [1 ,2 ]
Cao, Xin [2 ,3 ]
Zhang, Hongbin [1 ]
Lawrynczuk, Maciej
机构
[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Peoples R China
[2] Southwest Univ Sci & Technol, Sch Informat Engn, Mianyang 621010, Peoples R China
[3] Univ Elect Sci & Technol China, Sch Elect Sci & Engn, Chengdu 610054, Peoples R China
关键词
sparse system identification; proportionate; combined-step-size; convergence rate; ROBUST;
D O I
10.3390/electronics13010109
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
For sparse system identification, a memory-improved proportionate affine projection sign algorithm with a simplified, generalized correntropy induced metric (SGCI-M-IPAPSA) has good filtering performance. However, the SGCI-M-IPAPSA is based on a fixed step size and is not always the best choice. To overcome the limitation of a fixed step size in filtering precision and convergence speed under non-Gaussian impulsive interferences, in this paper, we apply the combined-step-size idea and a variable-step-size method based on the mean-square deviation to the SGCI-M-IPAPSA, respectively, and propose two new robust algorithms to enhance the filtering performance of the SGCI-M-IPAPSA. In addition, by combining the combined-step-size and proposed variable-step-size methods, we propose a fresh combined variable-step-size way and apply it to the SGCI-M-IPAPSA. The convergence of the proposed algorithms is also elaborated, and a conditional decision on the mean-square error is used to cope with abrupt changes. The better performances of the proposed algorithms than the conventional SGCI-M-IPAPSA in terms of the filtering accuracy and convergence rate are demonstrated with non-Gaussian impulsive interferences for sparse system identification, abrupt changes and colored inputs.
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页数:14
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