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Pemisahan Sumber Buta×Transformasi Fourier Jangka Pendek×
BidangPemprosesan IsyaratPemprosesan Isyarat
KeluargaProcess / pipelineProcess / pipeline
Tahun asal19941946
PengasasPierre ComonDennis Gabor
JenisUnsupervised signal decompositionTime-frequency signal analysis
Sumber perintisComon, P. (1994). Independent Component Analysis, a New Concept? Signal Processing, 36(3), 287–314. DOI ↗Gabor, D. (1946). Theory of Communication. Journal of the Institution of Electrical Engineers, 93(3), 429–457. link ↗
AliasBSS, Blind Signal Separation, Independent Component Analysis, ICASTFT, Windowed Fourier Transform, Time-Frequency Analysis
Berkaitan44
RingkasanBlind 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.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.
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ScholarGateBandingkan kaedah: Blind Source Separation · Short-Time Fourier Transform. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare