核磁共振波谱的非线性最小二乘拟合技术

W. Ge, H.K. Lee, O. Nalcioglu
{"title":"核磁共振波谱的非线性最小二乘拟合技术","authors":"W. Ge, H.K. Lee, O. Nalcioglu","doi":"10.1109/NSSMIC.1993.701854","DOIUrl":null,"url":null,"abstract":"A new iterative nonlinear least squares fitting technique is developed to fit the NMR free induction decay (FlD) signals in the time domain. The new technique makes it possible fitting all the parameters, e.g., frequencies, decay factors, amplitudes and phases, simultaneously. The corresponding initial values are obtained by linear prediction singular value decomposition (LPSVD)[ 11, which is a completely automatic process without any manual processing. The application of the new fitting technique yields a list of fitted parameters. Since the fitting process is carried out in the time domain, it is possible to fit truncated signals or the ones with shorter duration without a degradation of the resolution. The new technique also enables one to resolve close and overlapping frequency components which can not be resolved by fast Fourier transform (FFT) alone[2]. The FFT is used to provide initial frequencies for some weak components in case of low signal-to-noise ratio, but only as a complementary procedure.","PeriodicalId":287813,"journal":{"name":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Simultaneous Nonlinear Least Squares Fitting Technique For NMR Spectroscopy\",\"authors\":\"W. Ge, H.K. Lee, O. Nalcioglu\",\"doi\":\"10.1109/NSSMIC.1993.701854\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new iterative nonlinear least squares fitting technique is developed to fit the NMR free induction decay (FlD) signals in the time domain. The new technique makes it possible fitting all the parameters, e.g., frequencies, decay factors, amplitudes and phases, simultaneously. The corresponding initial values are obtained by linear prediction singular value decomposition (LPSVD)[ 11, which is a completely automatic process without any manual processing. The application of the new fitting technique yields a list of fitted parameters. Since the fitting process is carried out in the time domain, it is possible to fit truncated signals or the ones with shorter duration without a degradation of the resolution. The new technique also enables one to resolve close and overlapping frequency components which can not be resolved by fast Fourier transform (FFT) alone[2]. The FFT is used to provide initial frequencies for some weak components in case of low signal-to-noise ratio, but only as a complementary procedure.\",\"PeriodicalId\":287813,\"journal\":{\"name\":\"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NSSMIC.1993.701854\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NSSMIC.1993.701854","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

提出了一种新的迭代非线性最小二乘拟合方法,用于对核磁共振自由感应衰减信号进行时域拟合。新技术可以同时拟合所有参数,如频率、衰减因子、幅度和相位。相应的初始值由线性预测奇异值分解(LPSVD)得到[11],这是一个完全自动化的过程,不需要任何人工处理。新拟合技术的应用产生了一个拟合参数列表。由于拟合过程是在时域内进行的,因此可以在不降低分辨率的情况下拟合截断的信号或持续时间较短的信号。这项新技术还可以解决无法通过快速傅里叶变换(FFT)单独解决的紧密和重叠的频率分量[2]。FFT用于在低信噪比的情况下为一些弱分量提供初始频率,但仅作为补充程序。
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
Simultaneous Nonlinear Least Squares Fitting Technique For NMR Spectroscopy
A new iterative nonlinear least squares fitting technique is developed to fit the NMR free induction decay (FlD) signals in the time domain. The new technique makes it possible fitting all the parameters, e.g., frequencies, decay factors, amplitudes and phases, simultaneously. The corresponding initial values are obtained by linear prediction singular value decomposition (LPSVD)[ 11, which is a completely automatic process without any manual processing. The application of the new fitting technique yields a list of fitted parameters. Since the fitting process is carried out in the time domain, it is possible to fit truncated signals or the ones with shorter duration without a degradation of the resolution. The new technique also enables one to resolve close and overlapping frequency components which can not be resolved by fast Fourier transform (FFT) alone[2]. The FFT is used to provide initial frequencies for some weak components in case of low signal-to-noise ratio, but only as a complementary procedure.
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
Evaluation Of Wavelength Shifters For Spectral Separation Of Barium Fluoride Emissions High-speed Reconstruction Of SPECT Mages With A Tailored Piecewise Neural Network A 12-channel VMEBUS-based Pulse-height Analysis Module A Bipolar Analog Front-end Integrated Circuit For The SDC Silicon Tracker Detection geometry and reconstruction error in magnetic source imaging
×
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