Data Analysis and Filter Optimization for Pulse-Amplitude Measurement: A Case Study on High-Resolution X-ray Spectroscopy

Data Analysis and Filter Optimization for Pulse-Amplitude Measurement: A Case Study on High-Resolution X-ray Spectroscopy

In this study, we present a procedure to optimize a set of finite impulse response filter (FIR) coefficients for digital pulse-amplitude measurement. Such an optimized filter is designed using an adapted digital penalized least mean square (DPLMS) method. The effectiveness of the procedure is demons...

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Veröffentlicht in:Sensors (Basel, Switzerland) Switzerland), 2022-06, Vol.22 (13), p.4776
Hauptverfasser: Mannatunga, Kasun Sameera, Valinoti, Bruno, Florian Samayoa, Werner, Crespo, Maria Liz, Cicuttin, Andres, Folla Kamdem, Jerome, Garcia, Luis Guillermo, Carrato, Sergio
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Case studies
Cultural heritage
Data analysis
digital pulse processor (DPP)
digital signal processing (DSP)
Digitization
Energy
Energy spectra
FIR design
FIR filters
High resolution
Manganese
Mathematical models
Methods
Optimization
Personal computers
Photons
pulse-height analysis
Sensors
silicon drift detectors
Spectroscopic analysis
Spectrum analysis
X-ray spectroscopy
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Zusammenfassung:In this study, we present a procedure to optimize a set of finite impulse response filter (FIR) coefficients for digital pulse-amplitude measurement. Such an optimized filter is designed using an adapted digital penalized least mean square (DPLMS) method. The effectiveness of the procedure is demonstrated using a dataset from a case study on high-resolution X-ray spectroscopy based on single-photon detection and energy measurements. The energy resolutions of the Kα and Kβ lines of the Manganese energy spectrum have been improved by approximately 20%, compared to the reference values obtained by fitting individual photon pulses with the corresponding mathematical model.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22134776