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Journal ArticleDOI

A high-resolution quadratic time-frequency distribution for multicomponent signals analysis

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TLDR
A new kernel for the design of a high resolution time-frequency distribution (TFD) is introduced and it is shown that this distribution can solve problems that the Wigner-Ville distribution (WVD) or the spectrogram cannot.
Abstract
The paper introduces a new kernel for the design of a high resolution time-frequency distribution (TFD). We show that this distribution can solve problems that the Wigner-Ville distribution (WVD) or the spectrogram cannot. In particular, the proposed distribution can resolve two close signals in the time-frequency domain that the two other distributions cannot. Moreover, we show that the proposed distribution is more accurate than the WVD and the spectrogram in the estimation of the instantaneous frequency of a stepped FM signal embedded in additive Gaussian noise. Synthetic and real data collected from real-world applications are shown to validate the proposed distribution.

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Citations
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Journal ArticleDOI

Time--frequency feature representation using energy concentration: An overview of recent advances

TL;DR: Time-frequency domain signal processing using energy concentration as a feature is a very powerful tool and has been utilized in numerous applications and the expectation is that further research and applications of these algorithms will flourish in the near future.
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Linear and synchrosqueezed time-frequency representations revisited

TL;DR: It is shown that the higher concentration of the synchrosqueezed transforms does not seem to imply better resolution properties, so that the SWFT and SWT do not appear to provide any significant advantages over the original WFT and WT apart from a more visually appealing pictures.
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Time-frequency features for pattern recognition using high-resolution TFDs

TL;DR: Comparative results indicate that the new ( t, f ) features give better performance as compared to time-only or frequency-only features for the detection of abnormalities in newborn EEG signals.
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Underdetermined Blind Separation of Nondisjoint Sources in the Time-Frequency Domain

TL;DR: Two subspace-based algorithms for TF-nondisjoint sources are proposed: one uses quadratic TFDs and the other a linear TFD, and numerical performance of the proposed methods are provided highlighting their performance gain compared to existing ones.
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Advanced transformer winding deformation diagnosis: moving from off-line to on-line

TL;DR: In this article, the authors have concentrated on issues arising while on-line transformer winding deformation diagnosis is going to be applied on transformers with various kinds of techniques, such as frequency response analysis (FRA), short circuit impedance measurement and transfer function measurement.
References
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Journal ArticleDOI

Improved time-frequency representation of multicomponent signals using exponential kernels

TL;DR: In this article, a time-frequency distribution of L. Cohen's (1966) class is introduced, which is called exponential distribution (ED) after its exponential kernel function, and the authors interpret the ED from the spectral density-estimation point of view.
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The use of cone-shaped kernels for generalized time-frequency representations of nonstationary signals

TL;DR: Experimental results on simulated data and real speech show the advantages of the GTFRs with the cone-shaped kernels through comparisons to the spectrogram and the pseudo-Wigner distribution.
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Kernel design for reduced interference distributions

TL;DR: The authors present a class of time-frequency signal representations called the reduced interference distribution (RID), and a systematic procedure to create RID kernels, (or, equivalently, compute RIDs) is proposed.
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An efficient real-time implementation of the Wigner-Ville distribution

TL;DR: To evaluate the analytic signal required by the WVD analysis system, it is shown that the time domain definition implemented as a finite impulse response (FIR) filter is practical and more efficient than the frequency domain definition of the analytical signal.