A measure of some time-frequency distributions concentration
Signal Processing - Special section on digital signal processing for multimedia communications and services
A new subclass of complex-valued S-transform windows
Signal Processing - Special section: Advances in signal processing-assisted cross-layer designs
A basis for efficient representation of the S-transform
Digital Signal Processing
A window width optimized S-transform
EURASIP Journal on Advances in Signal Processing
Performance of quadratic time-frequency distributions as instantaneous frequency estimators
IEEE Transactions on Signal Processing
Localization of the complex spectrum: the S transform
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
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The Generalized S-transform (GST) applied in Instantaneous Frequency (IF) estimation is addressed in this paper. The analytical model for IF estimation error using the GST is established, which reveals that the estimation bias is determined directly by two variables: the standard deviation of the Gaussian window and the Instantaneous Frequency Rate (IFR) of the test signal. Based on the mathematical model, performance of the GST as an IF estimator is analyzed by three steps. Firstly, the time-varying expression for IF estimation Relative Error (RE) using the GST is derived. Secondly, the relationships between the RE and the signal's frequency characters are found. Thirdly, the effects of the window parameters on the RE are discussed. Consequently, a novel Adaptive Generalized S-transform (AGST) is developed, in which the window parameters are automatically adjusted in order to process signals with fast changing frequency characters. The proposed method is evaluated through several kinds of test signals to show its efficiency in IF estimation.