Sparse-Aware Bias-Compensated Adaptive Filtering Algorithms Using the Maximum Correntropy Criterion for Sparse System Identification with Noisy Input
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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ژورنال
عنوان ژورنال: Entropy
سال: 2018
ISSN: 1099-4300
DOI: 10.3390/e20060407