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Group-Constrained Maximum Correntropy Criterion Algorithms for Estimating Sparse Mix-Noised Channels
Wang, Yanyan; Li, Yingsong; Albu, Felix; Yang, Rui; Li, YS (reprint author), Harbin Engn Univ, Coll Informat & Commun Engn, Harbin 150001, Heilongjiang, Peoples R China.; Li, YS (reprint author), Chinese Acad Sci, Natl Space Sci Ctr, Beijing 100190, Peoples R China.
作者部门微波遥感部
发表期刊ENTROPY
2017
卷号19期号:8页码:432
ISSN1099-4300
语种英语
关键词Sparse Mcc Algorithms Mixed Noise Environment Zero-attracting Technique Norm Penalties
摘要A group-constrained maximum correntropy criterion (GC-MCC) algorithm is proposed on the basis of the compressive sensing (CS) concept and zero attracting (ZA) techniques and its estimating behavior is verified over sparse multi-path channels. The proposed algorithm is implemented by exerting different norm penalties on the two grouped channel coefficients to improve the channel estimation performance in a mixed noise environment. As a result, a zero attraction term is obtained from the expected l(0) and l(1) penalty techniques. Furthermore, a reweighting factor is adopted and incorporated into the zero-attraction term of the GC-MCC algorithm which is denoted as the reweighted GC-MCC (RGC-MMC) algorithm to enhance the estimation performance. Both the GC-MCC and RGC-MCC algorithms are developed to exploit well the inherent sparseness properties of the sparse multi-path channels due to the expected zero-attraction terms in their iterations. The channel estimation behaviors are discussed and analyzed over sparse channels in mixed Gaussian noise environments. The computer simulation results show that the estimated steady-state error is smaller and the convergence is faster than those of the previously reported MCC and sparse MCC algorithms.
收录类别SCI
文献类型期刊论文
条目标识符http://ir.nssc.ac.cn/handle/122/6128
专题微波遥感部
通讯作者Li, YS (reprint author), Harbin Engn Univ, Coll Informat & Commun Engn, Harbin 150001, Heilongjiang, Peoples R China.; Li, YS (reprint author), Chinese Acad Sci, Natl Space Sci Ctr, Beijing 100190, Peoples R China.
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Wang, Yanyan,Li, Yingsong,Albu, Felix,et al. Group-Constrained Maximum Correntropy Criterion Algorithms for Estimating Sparse Mix-Noised Channels[J]. ENTROPY,2017,19(8):432.
APA Wang, Yanyan,Li, Yingsong,Albu, Felix,Yang, Rui,Li, YS ,&Li, YS .(2017).Group-Constrained Maximum Correntropy Criterion Algorithms for Estimating Sparse Mix-Noised Channels.ENTROPY,19(8),432.
MLA Wang, Yanyan,et al."Group-Constrained Maximum Correntropy Criterion Algorithms for Estimating Sparse Mix-Noised Channels".ENTROPY 19.8(2017):432.
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