What is it about?
Depending on the measurement system, the deconvolution process can become an ill-posed problem, known as "Source Separation (SS)" in the field of signal processing, which occurs due to multiple source signals overlapping on one detector, such as "Crosstalk Signal". In this manuscript we have created new algorithm for retrieving the features of the electron spectrum using an L1 regularization (Sparse coding and decoding) and demonstrated that it can be applied to analyze actual electron energy spectrum.
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Why is it important?
A recent mathematical technique was applied to spectral deconvolution, and it is possible to analyze a spectrum that was difficult to deconvolute mathematically without initial value, until now.
Perspectives
L1 regularization may be unfamiliar to the readership. However, this is a general mathematics used for machine learning, and may be greatly used for measurement technology in the future. So, this algorithm has been shown to be useful for signal analysis where SS problem, and will greatly contribute to the development of data measurement and analysis in all physical fields.
Hironao Sakaki
National Institutes for Quantum and Radiological Science and Technology
Read the Original
This page is a summary of: New algorithm using L1 regularization for measuring electron energy spectra, Review of Scientific Instruments, July 2020, American Institute of Physics,
DOI: 10.1063/1.5144897.
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