Invention Grant
- Patent Title: Identification of one or more spectral features in a spectrum of a sample for a constituent analysis
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Application No.: US16762452Application Date: 2018-11-08
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Publication No.: US11293856B2Publication Date: 2022-04-05
- Inventor: Julius Krause , Robin Gruna
- Applicant: FRAUNHOFER-GESELLSCHAFT ZUR FÖRDERUNG DER ANGEWANDTEN FORSCHUNG E. V. , KARLSRUHER INSTITUT FÜR TECHNOLOGIE (KIT)
- Applicant Address: DE Munich; DE Karlsruhe
- Assignee: FRAUNHOFER-GESELLSCHAFT ZUR FÖRDERUNG DER ANGEWANDTEN FORSCHUNG E. V.,KARLSRUHER INSTITUT FÜR TECHNOLOGIE (KIT)
- Current Assignee: FRAUNHOFER-GESELLSCHAFT ZUR FÖRDERUNG DER ANGEWANDTEN FORSCHUNG E. V.,KARLSRUHER INSTITUT FÜR TECHNOLOGIE (KIT)
- Current Assignee Address: DE Munich; DE Karlsruhe
- Agency: Leydig, Voit & Mayer, Ltd.
- Priority: DE102017220103.7 20171110
- International Application: PCT/EP2018/080683 WO 20181108
- International Announcement: WO2019/092147 WO 20190516
- Main IPC: G01N21/31
- IPC: G01N21/31 ; G01J3/28

Abstract:
The invention relates to a method for identifying one or more spectral features in a spectrum (4, 5) of a sample for a constituent analysis of the sample, comprising providing the spectrum (4, 5), predefining an approximation function (6), which is a continuously differentiable mathematical function, respectively forming an (n−1)-th order derivative (7, 8, 9) of the spectrum (4, 5) and of the approximation function (6), wherein the number n>1, generating a correlation matrix (10) from the two (n−1)-th order derivatives (7, 8, 9), and respectively identifying the spectral feature or one of the spectral features in each case as a function of a local extremum (i) of the correlation matrix (10) for at least one extremum (i) of the correlation matrix (10) in order to simplify the constituent analysis of the sample.
Public/Granted literature
- US20210181093A1 IDENTIFICATION OF ONE OR MORE SPECTRAL FEATURES IN A SPECTRUM OF A SAMPLE FOR A CONSTITUENT ANALYSIS Public/Granted day:2021-06-17
Information query
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