LMS、NLMS、RLS和QR-RLS算法在车辆噪声抑制中的比较

R. Martínek, R. Kahankova, J. Nedoma, M. Fajkus, M. Skacel
{"title":"LMS、NLMS、RLS和QR-RLS算法在车辆噪声抑制中的比较","authors":"R. Martínek, R. Kahankova, J. Nedoma, M. Fajkus, M. Skacel","doi":"10.1145/3177457.3177502","DOIUrl":null,"url":null,"abstract":"The paper deals with the speech processing and adaptive filtration. For the analysis we used application implemented in both online and offline mode in LabVIEW. The experiments included comparison of the noise caused by electric car and diesel car which was measured and analyzed by means of Microphones NI 9234 and our application. We tested four different adaptive filters to cancel the noise and compared their efficiency. The criterion for comparing the efficiency of individual algorithms is primarily to increase the global signal to noise ratio (GSNR).","PeriodicalId":297531,"journal":{"name":"Proceedings of the 10th International Conference on Computer Modeling and Simulation","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Comparison of the LMS, NLMS, RLS, and QR-RLS algorithms for vehicle noise suppression\",\"authors\":\"R. Martínek, R. Kahankova, J. Nedoma, M. Fajkus, M. Skacel\",\"doi\":\"10.1145/3177457.3177502\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper deals with the speech processing and adaptive filtration. For the analysis we used application implemented in both online and offline mode in LabVIEW. The experiments included comparison of the noise caused by electric car and diesel car which was measured and analyzed by means of Microphones NI 9234 and our application. We tested four different adaptive filters to cancel the noise and compared their efficiency. The criterion for comparing the efficiency of individual algorithms is primarily to increase the global signal to noise ratio (GSNR).\",\"PeriodicalId\":297531,\"journal\":{\"name\":\"Proceedings of the 10th International Conference on Computer Modeling and Simulation\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-01-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 10th International Conference on Computer Modeling and Simulation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3177457.3177502\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 10th International Conference on Computer Modeling and Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3177457.3177502","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

本文主要研究语音处理和自适应滤波。为了进行分析,我们使用了在LabVIEW中在线和离线模式下实现的应用程序。实验包括用NI 9234对电动汽车和柴油车的噪声进行测量和分析,以及应用实例。我们测试了四种不同的自适应滤波器来消除噪声,并比较了它们的效率。比较各个算法效率的标准主要是提高全局信噪比(GSNR)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Comparison of the LMS, NLMS, RLS, and QR-RLS algorithms for vehicle noise suppression
The paper deals with the speech processing and adaptive filtration. For the analysis we used application implemented in both online and offline mode in LabVIEW. The experiments included comparison of the noise caused by electric car and diesel car which was measured and analyzed by means of Microphones NI 9234 and our application. We tested four different adaptive filters to cancel the noise and compared their efficiency. The criterion for comparing the efficiency of individual algorithms is primarily to increase the global signal to noise ratio (GSNR).
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
期刊最新文献
rTuner: A Performance Enhancement of MapReduce Job Sensitivity Analysis of a Causality-Informed Genetic Programming Ensemble for Inferring Dynamical Systems Improving Efficiency of TV PCB Assembly Line Using a Discrete Event Simulation Approach: A Case Study Workflow for Developing High-Resolution 3D City Models in Korea Standard Values of Service Level of Intersection for Collection and Distribution Roads of Container Terminals
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1