使用牛顿型算法的新型自适应检测滤波器

Proceedings of SOUTHEASTCON '94 Pub Date : 1994-04-10 DOI:10.1109/SECON.1994.324345

C. Lindquist, June-Ming Shen

{"title":"使用牛顿型算法的新型自适应检测滤波器","authors":"C. Lindquist, June-Ming Shen","doi":"10.1109/SECON.1994.324345","DOIUrl":null,"url":null,"abstract":"An adaptive detection filter detects the presence of a desired signal in noisy environment. In this paper, we present several detection filtering algorithms in the time domain. Our algorithm's vector forms are compared with gradient search methods include Newton, steepest descent and least-mean-square. We find that our algorithms are of the Newton-type.<<ETX>>","PeriodicalId":119615,"journal":{"name":"Proceedings of SOUTHEASTCON '94","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"New adaptive detection filters using Newton-type algorithms\",\"authors\":\"C. Lindquist, June-Ming Shen\",\"doi\":\"10.1109/SECON.1994.324345\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An adaptive detection filter detects the presence of a desired signal in noisy environment. In this paper, we present several detection filtering algorithms in the time domain. Our algorithm's vector forms are compared with gradient search methods include Newton, steepest descent and least-mean-square. We find that our algorithms are of the Newton-type.<<ETX>>\",\"PeriodicalId\":119615,\"journal\":{\"name\":\"Proceedings of SOUTHEASTCON '94\",\"volume\":\"100 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of SOUTHEASTCON '94\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SECON.1994.324345\",\"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 SOUTHEASTCON '94","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.1994.324345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

自适应检测滤波器在噪声环境中检测所需信号的存在。本文给出了几种时域检测滤波算法。将该算法的向量形式与牛顿、最陡下降和最小均方差等梯度搜索方法进行了比较。我们发现我们的算法是牛顿型的。

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

微信好友朋友圈 QQ好友复制链接

本刊更多论文

New adaptive detection filters using Newton-type algorithms

An adaptive detection filter detects the presence of a desired signal in noisy environment. In this paper, we present several detection filtering algorithms in the time domain. Our algorithm's vector forms are compared with gradient search methods include Newton, steepest descent and least-mean-square. We find that our algorithms are of the Newton-type.<>

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

Proceedings of SOUTHEASTCON '94

自引率

0.00%

发文量

期刊最新文献

The use of wavelet transform as a preprocessor for the neural network detection of EEG spikes An output unit for low frequency square wave electronic ballasts The IBM Personal Communicator-design considerations Accelerating conversations for fault-tolerant concurrent software Application of three dimensional image analysis to the mammalian cell nucleus