Incorporation of a positivity constraint into a Kalman-filter-based algorithm for correction of spectrometric data

Improving the resolution of spectrometric analyses by numerical processing of spectrometric data subject to systematic errors of an instrumental type, as well as to random errors, is addressed. It is assumed that the model of the spectrometric data has the form of an integral, convolution-type equat...

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Vydáno v:	IEEE transactions on instrumentation and measurement Ročník 44; číslo 1; s. 2 - 7
Hlavní autoři:	Massicotte, D., Morawski, R.Z., Barwicz, A.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York, NY IEEE 01.02.1995 Institute of Electrical and Electronics Engineers
Témata:	Absorption Algorithm design and analysis Computers in experimental physics Data analysis: algorithms and implementation; data management Error correction Exact sciences and technology Instruments Instruments, apparatus, components and techniques common to several branches of physics and astronomy Integral equations Light sources Mass spectroscopy Optical filters Optical recording Physics Spectroscopy Algorithms Experimental data Numerical computation Spectral resolution Signal-to-noise ratio Data processing Error correction Experimental study Kalman filters Constrained optimization
ISSN:	0018-9456
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Abstract	Improving the resolution of spectrometric analyses by numerical processing of spectrometric data subject to systematic errors of an instrumental type, as well as to random errors, is addressed. It is assumed that the model of the spectrometric data has the form of an integral, convolution-type equation of the first kind. The method for improving the resolution consists of numerically solving this equation on the basis of the acquired data. A new algorithm for dealing with this problem is proposed; it is based on the Kalman filter constrained in such a way that the negative values of the solution are suppressed. The efficiency of this constrained algorithm is demonstrated using both synthetic and real-world data.< >
AbstractList	Improving the resolution of spectrometric analyses by numerical processing of spectrometric data subject to systematic errors of an instrumental type, as well as to random errors, is addressed. It is assumed that the model of the spectrometric data has the form of an integral, convolution-type equation of the first kind. The method for improving the resolution consists of numerically solving this equation on the basis of the acquired data. A new algorithm for dealing with this problem is proposed; it is based on the Kalman filter constrained in such a way that the negative values of the solution are suppressed. The efficiency of this constrained algorithm is demonstrated using both synthetic and real-world data.< > Improving the resolution of spectrometric analyses by numerical processing of spectrometric data subject to systematic errors of an instrumental type, as well as to random errors, is addressed. It is assumed that the model of the spectrometric data has the form of an integral, convolution-type equation of the first kind. The method for improving the resolution consists of numerically solving this equation on the basis of the acquired data. A new algorithm for dealing with this problem is proposed; it is based on the Kalman filter constrained in such a way that the negative values of the solution are suppressed. The efficiency of this constrained algorithm is demonstrated using both synthetic and real-world data
Author	Massicotte, D. Barwicz, A. Morawski, R.Z.
Author_xml	– sequence: 1 givenname: D. surname: Massicotte fullname: Massicotte, D. organization: Dept. d'Ingenierie, Quebec Univ., Trois-Rivieres, Que., Canada – sequence: 2 givenname: R.Z. surname: Morawski fullname: Morawski, R.Z. – sequence: 3 givenname: A. surname: Barwicz fullname: Barwicz, A.
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Cites_doi	10.1049/el:19830062 10.1109/TASSP.1985.1164564 10.1080/01483918408067050 10.1109/19.87019 10.1016/0263-2241(91)90035-O 10.1109/TASSP.1985.1164671
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Keywords	Spectroscopy Algorithms Experimental data Numerical computation Spectral resolution Signal-to-noise ratio Data processing Error correction Experimental study Kalman filters Constrained optimization
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SubjectTerms	Absorption Algorithm design and analysis Computers in experimental physics Data analysis: algorithms and implementation; data management Error correction Exact sciences and technology Instruments Instruments, apparatus, components and techniques common to several branches of physics and astronomy Integral equations Light sources Mass spectroscopy Optical filters Optical recording Physics
Title	Incorporation of a positivity constraint into a Kalman-filter-based algorithm for correction of spectrometric data
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