基于扩散的分布式MVDR波束形成器

Matthew O'Connor, W. Kleijn
{"title":"基于扩散的分布式MVDR波束形成器","authors":"Matthew O'Connor, W. Kleijn","doi":"10.1109/ICASSP.2014.6853709","DOIUrl":null,"url":null,"abstract":"Advances in hardware and communication technology make distributed sound acquisition increasingly attractive. We describe a distributed beamforming method based on the diffusion adaptation paradigm. In contrast to existing distributed beamforming methods, the method does not impose conditions on the topology or the structure of the network nor does it require knowledge of the noise co-variance matrix. The algorithm can continuously track changes in the noise covariance matrix, making it suitable for a practical, dynamic environment. It will typically perform one iteration per signal sample, limiting communication requirements. Our experiments confirm the effectiveness of the method.","PeriodicalId":6545,"journal":{"name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"29 1","pages":"810-814"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"Diffusion-based distributed MVDR beamformer\",\"authors\":\"Matthew O'Connor, W. Kleijn\",\"doi\":\"10.1109/ICASSP.2014.6853709\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Advances in hardware and communication technology make distributed sound acquisition increasingly attractive. We describe a distributed beamforming method based on the diffusion adaptation paradigm. In contrast to existing distributed beamforming methods, the method does not impose conditions on the topology or the structure of the network nor does it require knowledge of the noise co-variance matrix. The algorithm can continuously track changes in the noise covariance matrix, making it suitable for a practical, dynamic environment. It will typically perform one iteration per signal sample, limiting communication requirements. Our experiments confirm the effectiveness of the method.\",\"PeriodicalId\":6545,\"journal\":{\"name\":\"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)\",\"volume\":\"29 1\",\"pages\":\"810-814\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP.2014.6853709\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2014.6853709","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27

摘要

硬件和通信技术的进步使得分布式声音采集越来越有吸引力。提出了一种基于扩散自适应范式的分布式波束形成方法。与现有的分布式波束形成方法相比,该方法不需要对网络的拓扑或结构施加条件,也不需要了解噪声协方差矩阵。该算法可以连续跟踪噪声协方差矩阵的变化,适用于实际的动态环境。它通常对每个信号采样执行一次迭代,从而限制了通信需求。我们的实验证实了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diffusion-based distributed MVDR beamformer
Advances in hardware and communication technology make distributed sound acquisition increasingly attractive. We describe a distributed beamforming method based on the diffusion adaptation paradigm. In contrast to existing distributed beamforming methods, the method does not impose conditions on the topology or the structure of the network nor does it require knowledge of the noise co-variance matrix. The algorithm can continuously track changes in the noise covariance matrix, making it suitable for a practical, dynamic environment. It will typically perform one iteration per signal sample, limiting communication requirements. Our experiments confirm the effectiveness of the method.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信