Implementation of the Prony Method for Signal Deconvolution

被引:2
|
作者
Wilson, Emma [1 ,2 ]
Conneely, Thomas M. [2 ]
Mudrov, Andrey [1 ]
Tyukin, Ivan [1 ]
机构
[1] Univ Leicester, Dept Math, Univ Rd, Leicester LE1 7RH, Leics, England
[2] Photek Ltd, 26 Castleham Rd, St Leonards On Sea TN38 9NS, E Sussex, England
来源
IFAC PAPERSONLINE | 2019年 / 52卷 / 29期
基金
“创新英国”项目;
关键词
Statistical data analysis; Modeling and identification; Errors in variables identification; Time series modeling; Software for system identification; PARAMETER-ESTIMATION;
D O I
10.1016/j.ifacol.2019.12.661
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Modern implementations of the Prony method have been used in the statistical analysis of sinusoidal and/or exponential signals distorted with noise. Modern implementations are auto-regressive, using a series of matrix calculations and least-squares to calculate the values of interest from a signal; the frequency, decay constant, initial amplitude, and phase. In cavity ring-down spectroscopy, the frequency and decay constant of an exponentially decaying sinusoidal signal need to be obtained, in order to identify molecules and the chirality of these molecules, which may be applied in, for instance, development of pharmaceuticals. This method is applicable to signals from other fields - signals which are sinusoidal or exponential in nature. An implementation of the Prony method for cavity ring-down spectroscopy has been developed and characterised in Python. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码:269 / 273
页数:5
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