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Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Transformée de Fourier à court terme× | Séparation aveugle de sources× | |
|---|---|---|
| Domaine | Traitement du signal | Traitement du signal |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 1946 | 1994 |
| Auteur d'origine≠ | Dennis Gabor | Pierre Comon |
| Type≠ | Time-frequency signal analysis | Unsupervised signal decomposition |
| Source fondatrice≠ | Gabor, D. (1946). Theory of Communication. Journal of the Institution of Electrical Engineers, 93(3), 429–457. link ↗ | Comon, P. (1994). Independent Component Analysis, a New Concept? Signal Processing, 36(3), 287–314. DOI ↗ |
| Alias≠ | STFT, Windowed Fourier Transform, Time-Frequency Analysis | BSS, Blind Signal Separation, Independent Component Analysis, ICA |
| Apparentées | 4 | 4 |
| Résumé≠ | The Short-Time Fourier Transform (STFT) is a fundamental signal analysis technique that computes the frequency content of a signal as it evolves over time by applying the Fourier transform to short, overlapping windows of the signal. Introduced conceptually by Dennis Gabor in 1946, the STFT provides a time-frequency representation essential for analyzing non-stationary signals where frequency content changes over time. | Blind Source Separation (BSS) is a signal processing technique that recovers original signals from their unknown mixture without detailed knowledge of the mixing process. Through the framework of Independent Component Analysis (ICA), BSS recovers statistically independent source signals using only the assumption that sources are independent and non-Gaussian. First formalized by Pierre Comon in 1994, BSS has become essential for applications from audio separation to biomedical signal analysis. |
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