Maximum correntropy criterion based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian environments
نویسندگان
چکیده
منابع مشابه
Maximum correntropy criterion based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian environments
Sparse adaptive channel estimation problem is one of the most important topics in broadband wireless communications systems due to its simplicity and robustness. So far many sparsity-aware channel estimation algorithms have been developed based on the well-known minimum mean square error (MMSE) criterion, such as the zero-attracting least mean square (ZALMS),which are robust under Gaussian assu...
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Tingping Zhang 1,2,* and Guan Gui 3 1 School of Information Science and Engineering, Chongqing Jiaotong University, Chongqing 400074, China 2 College of Computer Science, Chongqing University, Chongqing 400044, China 3 Institute of Signal Transmission and Processing, College of Telecommunication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, Chi...
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The maximum correntropy criterion (MCC) has recently been successfully applied to adaptive filtering. Adaptive algorithms under MCC show strong robustness against large outliers. In this work, we apply the MCC criterion to develop a robust Hammerstein adaptive filter. Compared with the traditional Hammerstein adaptive filters, which are usually derived based on the well-known mean square error ...
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ژورنال
عنوان ژورنال: Journal of the Franklin Institute
سال: 2015
ISSN: 0016-0032
DOI: 10.1016/j.jfranklin.2015.03.039