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Paper Detail

Paper:	SPTM-P5.12
Session:	Time-Frequency Transforms and Operators
Time:	Wednesday, May 17, 14:00 - 16:00
Presentation:	Poster
Topic:	Signal Processing Theory and Methods: Non-stationary Signals and Time-Frequency Analysis
Title:	Short Time Fourier Transform Probability Distribution for Time-Frequency Segmentation
Authors:	Fabien Millioz, Julien Huillery, Nadine Martin, Laboratory of Image and Signal (LIS), France
Abstract:	Taking as signal model the sum of a non-stationnary deterministic part embedded in a white Gaussian noise, this paper presents the distribution of the coefficients of the Short Time Fourier Transform (STFT), which is used to determine the maximum likelihood estimator of the noise level. We then propose an automatic segmentation algorithm of the real and imaginary parts of the STFT based on statistical features, which is an alternative to the spectrogram segmentations considered as image segmentations. Exemples of segmented time-frequency space are presented on a simulated signal and on a dolphin whistle.