| Autor: |
Moskovsky, S.B., Sergeev, A.N., Vasiliev, I.D. |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| DOI: |
10.34660/inf.2023.43.63.012 |
| Popis: |
Diffractometric analysis is widely used in materials science to study the crystal structure and state of the surface of materials. The wavelet transform allows you to decompose the signal into different scales and reduce noise, while maintaining information about the signal structure. Neural networks trained on wavelet-transformed data can efficiently process diffraction patterns, taking into account different scales and data structure, increasing the possibilities of simple transformation in the speed and volume of data being processed. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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