A robust least mean M-estimate adaptive filtering algorithm based on geometric algebra for system identification

Author(s):  
shaohui Lv ◽  
Haiquan Zhao
2014 ◽  
Vol 602-605 ◽  
pp. 2411-2414
Author(s):  
Qing Xia ◽  
Yun Lin ◽  
Hui Luo

In this passage we propose a computationally efficient adaptive filtering algorithm for sparse system identification.The algorithm is based on dichotomous coordinate descent iterations, reweighting iterations,iterative support detection.In order to reduce the complexity we try to discuss in the support.we suppose the support is partial,and partly erroneous.Then we can use the iterative support detection to solve the problem.Numerical examples show that the proposed method achieves an identification performance better than that of advanced sparse adaptive filters (l1-RLS,l0-RLS) and its performance is close to the oracle performance.


IEEE Access ◽  
2020 ◽  
pp. 1-1
Author(s):  
Rui Wang ◽  
Meixiang Liang ◽  
Yinmei He ◽  
Xiangyang Wang ◽  
Wenming Cao

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 78298-78310 ◽  
Author(s):  
Rui Wang ◽  
Yinmei He ◽  
Chenyang Huang ◽  
Xiangyang Wang ◽  
Wenming Cao

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