检索结果-南通市图书馆

A powerful adaptive microbiome-based association test for microbial association signals with diverse sparsity levels

引用

Journal of Genetics and Genomics 2021年第9期48卷 851-859页

作者： Han Sun Xiaoyun Huang Lingling Fu Ban Huo Tingting He Xingpeng Jiang Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning Central China Normal UniversityWuhan 430079China School of Computer Central China Normal UniversityWuhan 430079China School of Mathematics and Statistics Central China Normal UniversityWuhan 430079China Collaborative&Innovative Center for Educational Technology Central China Normal UniversityWuhan 430079China National Language Resources Monitoring&Research Center for Network Media Central China Normal UniversityWuhan 430079China

The dysbiosis of microbiome may have negative effects on a host *** microbes related to the host phenotype are regarded as microbial association ***,statistical methods based on microbiome-phenotype association tests have been extensively developed to detect these association ***,the currently available methods do not perform well to detect microbial association signals when dealing with diverse sparsity levels(i.e.,sparse,low sparse,non-sparse).Actually,the real association patterns related to different host phenotypes are not ***,we propose a powerful and adaptive microbiome-based association test to detect microbial association signals with diverse sparsity levels,designated as *** particular,we define probability degree to measure the associations between microbes and the host phenotype and introduce the adaptive weighted sum of powered score tests by considering both probability degree and phylogenetic *** design numerous simulation experiments for the task of detecting association signals with diverse sparsity levels to prove the performance of the *** find that type I error rates can be well-controlled and MiATDS shows superior efficiency on the *** applying to real data analysis,MiATDS displays reliable practicability *** R package is available at https://***/XiaoyunHuang33/MiATDS.

关键词： Microbiome association Association test sparsity level Phylogenetic relevance Phenotype

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

A sparsity AND COMPRESSION RATIO JOINT ADJUSTMENT METHOD FOR COLLABORATIVE SPECTRUM SENSING

引用

Journal of Electronics(China) 2012年第6期29卷 604-610页

作者： Chi Jingxiu Zhang Jianwu Xu Xiaorong College of Telecommunication Engineering Hangzhou Dianzi University Institute of Information and Communication Engineering Zhejiang University

Spectrum sensing is the fundamental task for Cognitive Radio (CR). To overcome the challenge of high sampling rate in traditional spectral estimation methods, Compressed Sensing (CS) theory is developed. A sparsity and compression ratio joint adjustment algorithm for compressed spectrum sensing in CR network is investigated, with the hypothesis that the sparsity level is unknown as priori knowledge at CR terminals. As perfect spectrum reconstruction is not necessarily required during spectrum detection process, the proposed algorithm only performs a rough estimate of sparsity level. Meanwhile, in order to further reduce the sensing measurement, different compression ratios for CR terminals with varying Signal-to-Noise Ratio (SNR) are considered. The proposed algorithm, which optimizes the compression ratio as well as the estimated sparsity level, can greatly reduce the sensing measurement without degrading the detection performance. It also requires less steps of iteration for convergence. Corroborating simulation results are presented to testify the effectiveness of the proposed algorithm for collaborative spectrum sensing.

关键词： Collaborative spectrum sensing sparsity level Compression ratio Joint adjustment method

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：