基于加权最小二乘的布里渊散射光谱信息的LM算法研究

Wei Yu, Shengpeng Wan, B. Li, Lin Zhong, Wengang Hu, Wei Wang
{"title":"基于加权最小二乘的布里渊散射光谱信息的LM算法研究","authors":"Wei Yu, Shengpeng Wan, B. Li, Lin Zhong, Wengang Hu, Wei Wang","doi":"10.1109/SOPO.2012.6270510","DOIUrl":null,"url":null,"abstract":"Compare LM algorithm in reference to the iteration because of slow convergence speed,low convergence precision,poor stability,easy to get bad data influence each other about the Weighted Least Squares. This paper introduces the LM algorithm of based on Weighted Least Squares. The algorithm is applied to Brillouin scattering spectra information processing. The LM algorithm is the improvement algorithm of the Weighted Least Squares.This paper expounds the principle of Weighted Least Squares and LM algorithm . That introduces the LM algorithm of parameters adjustment method and its convergence judgement basis . Finally,the paper gives corresponding simulation results and analysis according to the examples . The LM algorithm has better convergence and stability comparing with the traditional Weighted Least Squares. The LM algorithm has rapid convergence and higher precision and saves time for measurement influence Brillouin scattering parameters.","PeriodicalId":159850,"journal":{"name":"2012 Symposium on Photonics and Optoelectronics","volume":"165 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The LM Algorithm Research in Brillouin Scattering Spectra Information Based on the Weighted Least Squares\",\"authors\":\"Wei Yu, Shengpeng Wan, B. Li, Lin Zhong, Wengang Hu, Wei Wang\",\"doi\":\"10.1109/SOPO.2012.6270510\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Compare LM algorithm in reference to the iteration because of slow convergence speed,low convergence precision,poor stability,easy to get bad data influence each other about the Weighted Least Squares. This paper introduces the LM algorithm of based on Weighted Least Squares. The algorithm is applied to Brillouin scattering spectra information processing. The LM algorithm is the improvement algorithm of the Weighted Least Squares.This paper expounds the principle of Weighted Least Squares and LM algorithm . That introduces the LM algorithm of parameters adjustment method and its convergence judgement basis . Finally,the paper gives corresponding simulation results and analysis according to the examples . The LM algorithm has better convergence and stability comparing with the traditional Weighted Least Squares. The LM algorithm has rapid convergence and higher precision and saves time for measurement influence Brillouin scattering parameters.\",\"PeriodicalId\":159850,\"journal\":{\"name\":\"2012 Symposium on Photonics and Optoelectronics\",\"volume\":\"165 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Symposium on Photonics and Optoelectronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SOPO.2012.6270510\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Symposium on Photonics and Optoelectronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOPO.2012.6270510","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

与LM算法相比,加权最小二乘算法由于收敛速度慢、收敛精度低、稳定性差、容易得到不良数据等缺点相互影响。本文介绍了一种基于加权最小二乘的LM算法。将该算法应用于布里渊散射光谱信息的处理。LM算法是加权最小二乘的改进算法。本文阐述了加权最小二乘和LM算法的原理。介绍了参数平差法的LM算法及其收敛性判断依据。最后,根据算例给出了相应的仿真结果和分析。与传统的加权最小二乘算法相比,LM算法具有更好的收敛性和稳定性。LM算法收敛速度快,精度高,节省了测量布里渊散射影响参数的时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The LM Algorithm Research in Brillouin Scattering Spectra Information Based on the Weighted Least Squares
Compare LM algorithm in reference to the iteration because of slow convergence speed,low convergence precision,poor stability,easy to get bad data influence each other about the Weighted Least Squares. This paper introduces the LM algorithm of based on Weighted Least Squares. The algorithm is applied to Brillouin scattering spectra information processing. The LM algorithm is the improvement algorithm of the Weighted Least Squares.This paper expounds the principle of Weighted Least Squares and LM algorithm . That introduces the LM algorithm of parameters adjustment method and its convergence judgement basis . Finally,the paper gives corresponding simulation results and analysis according to the examples . The LM algorithm has better convergence and stability comparing with the traditional Weighted Least Squares. The LM algorithm has rapid convergence and higher precision and saves time for measurement influence Brillouin scattering parameters.
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