NDLI: Circularity of the STFT and Spectral Kurtosis for Time-Frequency Segmentation in Gaussian Environment

Content Provider	IEEE Xplore Digital Library
Author	Millioz, F. Martin, N.
Copyright Year	1991
Abstract	This paper investigates the circularity of short time Fourier transform (STFT) coefficients noise only, and proposes a modified STFT such that all coefficients coming from white Gaussian noise are circular. In order to use the spectral kurtosis (SK) as a Gaussianity test to check if signal points are present in a set of STFT points, we consider the SK of complex circular random variables, and its link with the kurtosis of the real and imaginary parts. We show that the variance of the SK is smaller than the variance of the kurtosis estimated from both real and imaginary parts. The effect of the noncircularity of Gaussian variables upon the spectral kurtosis of STFT coefficients is studied, as well as the effect of signal presence. Finally, a time-frequency segmentation algorithm based on successive iterations of noise variance estimation and time-frequency coefficients detection is proposed. The iterations are stopped when the spectral kurtosis on nondetected points reaches zero. Examples of segmented time-frequency space are presented on a dolphin whistle and on a simulated signal in nonwhite and nonstationary Gaussian noise.
Sponsorship	IEEE Signal Processing Society
Starting Page	515
Ending Page	524
Page Count	10
File Size	1120604
File Format	PDF
ISSN	1053587X
Volume Number	59
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-02-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Time frequency analysis Fourier transforms Equations Spectrogram Correlation Gaussian noise time-frequency segmentation Circularity short time Fourier transform (STFT) spectral kurtosis statistical segmentation time-frequency analysis
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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