Time-Frequency Analysis of Non-Uniformly Sampled Signals via Sample Density Adaptation
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arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866908816567697408 |
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| author | Kulkarni, Ashwini Nannuru, Santosh |
| author_facet | Kulkarni, Ashwini Nannuru, Santosh |
| contents | The analysis of non-stationary signals in non-uniformly sampled data is a challenging task. Time-integrated methods, such as the generalised Lomb-Scargle (GLS) periodogram, provide a robust statistical assessment of persistent periodicities but are insensitive to transient events. Conversely, existing time-frequency methods often rely on fixed-duration windows or interpolation, which can be suboptimal for non-uniform data. We introduce the non-uniform Stockwell-transform (NUST), a time-frequency framework that applies a localized density adaptive spectral analysis directly to non-uniformly sampled data. NUST employs a doubly adaptive window that adjusts its width based on both frequency and local data density, providing detailed time-frequency information for both transient and persistent signals. We validate the NUST on numerous non-uniformly sampled synthetic signals, demonstrating its superior time-localization performance compared to GLS. Furthermore, we apply NUST to HARPS radial velocity data of the multi-planetary system HD 10180, successfully distinguishing coherent planetary signals from stellar activity. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_22891 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Time-Frequency Analysis of Non-Uniformly Sampled Signals via Sample Density Adaptation Kulkarni, Ashwini Nannuru, Santosh Signal Processing Instrumentation and Methods for Astrophysics The analysis of non-stationary signals in non-uniformly sampled data is a challenging task. Time-integrated methods, such as the generalised Lomb-Scargle (GLS) periodogram, provide a robust statistical assessment of persistent periodicities but are insensitive to transient events. Conversely, existing time-frequency methods often rely on fixed-duration windows or interpolation, which can be suboptimal for non-uniform data. We introduce the non-uniform Stockwell-transform (NUST), a time-frequency framework that applies a localized density adaptive spectral analysis directly to non-uniformly sampled data. NUST employs a doubly adaptive window that adjusts its width based on both frequency and local data density, providing detailed time-frequency information for both transient and persistent signals. We validate the NUST on numerous non-uniformly sampled synthetic signals, demonstrating its superior time-localization performance compared to GLS. Furthermore, we apply NUST to HARPS radial velocity data of the multi-planetary system HD 10180, successfully distinguishing coherent planetary signals from stellar activity. |
| title | Time-Frequency Analysis of Non-Uniformly Sampled Signals via Sample Density Adaptation |
| topic | Signal Processing Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2509.22891 |