中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Performance bounds of distributed adaptive filters with cooperative correlated signals

文献类型:期刊论文

作者Chen, Chen1; Liu, Zhixin2; Guo, Lei2; Liu Zhixin; Guo Lei
刊名SCIENCE CHINA-INFORMATION SCIENCES
出版日期2016-11-01
卷号59期号:11页码:10
关键词distributed adaptive filters LMS random process stochastic stability graph connectivity
ISSN号1674-733X
DOI10.1007/s11432-016-0050-9
英文摘要In this paper, we studied the least mean-square-based distributed adaptive filters, aiming at collectively estimating a sequence of unknown signals (or time-varying parameters) from a set of noisy measurements obtained through distributed sensors. The main contribution of this paper to relevant literature is that under a general stochastic cooperative signal condition, stability and performance bounds are established for distributed filters with general connected networks without stationarity or independency assumptions imposed on the regression signals.
资助项目National Natural Science Foundation of China[61273221] ; National Basic Research Program of China (973)[2014CB845302]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000402523000001
出版者SCIENCE PRESS
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/25704]  
专题系统科学研究所
国家数学与交叉科学中心
通讯作者Guo, Lei
作者单位1.Huawei Technol Co Ltd, Lab 2012, Shannon Cognit Comp Lab, Beijing 100085, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Chen, Chen,Liu, Zhixin,Guo, Lei,et al. Performance bounds of distributed adaptive filters with cooperative correlated signals[J]. SCIENCE CHINA-INFORMATION SCIENCES,2016,59(11):10.
APA Chen, Chen,Liu, Zhixin,Guo, Lei,Liu Zhixin,&Guo Lei.(2016).Performance bounds of distributed adaptive filters with cooperative correlated signals.SCIENCE CHINA-INFORMATION SCIENCES,59(11),10.
MLA Chen, Chen,et al."Performance bounds of distributed adaptive filters with cooperative correlated signals".SCIENCE CHINA-INFORMATION SCIENCES 59.11(2016):10.

入库方式: OAI收割

来源:数学与系统科学研究院

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