Discovering and modeling hidden periodicities in science data
Abstract Hidden periodicities in science data have long been a popular topic of investigation. The popularity stems from the fact that detecting and characterizing periodicities can provide a means for extracting information from science data—information that might not otherwise be accessible. In ot...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-04-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13634-025-01207-w |
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