遥感系统中信号处理的自回归谱算法

V. I. Elfimov, V. K. Kochkina
{"title":"遥感系统中信号处理的自回归谱算法","authors":"V. I. Elfimov, V. K. Kochkina","doi":"10.1109/CRMICO.2014.6959839","DOIUrl":null,"url":null,"abstract":"Classical spectral methods of assessment are among the most sustainable methods. They apply to almost all classes of signals and noise, with fixed properties. The reason of application of the parametric models of random processes is due to the possibility of receipt on the basis of these models more accurate spectral estimates than it is possible by using the classical methods of spectral estimation.","PeriodicalId":6662,"journal":{"name":"2014 24th International Crimean Conference Microwave & Telecommunication Technology","volume":"129 1","pages":"1221-1222"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Autoregressive spectral algorithms of signal processing in systems of remote sensing\",\"authors\":\"V. I. Elfimov, V. K. Kochkina\",\"doi\":\"10.1109/CRMICO.2014.6959839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Classical spectral methods of assessment are among the most sustainable methods. They apply to almost all classes of signals and noise, with fixed properties. The reason of application of the parametric models of random processes is due to the possibility of receipt on the basis of these models more accurate spectral estimates than it is possible by using the classical methods of spectral estimation.\",\"PeriodicalId\":6662,\"journal\":{\"name\":\"2014 24th International Crimean Conference Microwave & Telecommunication Technology\",\"volume\":\"129 1\",\"pages\":\"1221-1222\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 24th International Crimean Conference Microwave & Telecommunication Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CRMICO.2014.6959839\",\"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 24th International Crimean Conference Microwave & Telecommunication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRMICO.2014.6959839","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

经典的光谱评估方法是最可持续的方法之一。它们适用于几乎所有类别的信号和噪声,具有固定的性质。随机过程的参数模型之所以被应用,是因为在这些模型的基础上可以得到比经典的谱估计方法更精确的谱估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autoregressive spectral algorithms of signal processing in systems of remote sensing
Classical spectral methods of assessment are among the most sustainable methods. They apply to almost all classes of signals and noise, with fixed properties. The reason of application of the parametric models of random processes is due to the possibility of receipt on the basis of these models more accurate spectral estimates than it is possible by using the classical methods of spectral estimation.
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