Group-Constrained Maximum Correntropy Criterion Algorithms for Estimating Sparse Mix-Noised Channels
文献类型：期刊论文
| 作者 | 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. |
| 刊名 | ENTROPY
 |
| 出版日期 | 2017 |
| 卷号 | 19期号:8页码:432 |
| 关键词 | Sparse Mcc Algorithms Mixed Noise Environment Zero-attracting Technique Norm Penalties |
| ISSN号 | 1099-4300 |
| 英文摘要 | 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. |
| 语种 | 英语 |
| 资助机构 | PhD Student Research and Innovation Fund of the Fundamental Research Funds for the Central Universities [HEUGIP201707] ; National Key Research and Development Program of China-Government Corporation Special Program [2016YFE0111100] ; National Science Foundation of China [61571149] ; Science and Technology innovative Talents Foundation of Harbin [2016RAXXJ044] ; Projects for the Selected Returned Overseas Chinese Scholars of Heilongjiang Province ; MOHRSS of China |
| 源URL | [http://ir.nssc.ac.cn/handle/122/6128]  |
| 专题 | 国家空间科学中心_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. |
| 推荐引用方式 GB/T 7714 | 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. |
入库方式： OAI收割
来源：国家空间科学中心
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