Time-frequency (TF) signal analysis has recently experienced a slow awakening followed by
an accelerating development of interest. This paper discusses a specific concept applied to …

Many time-frequency representations fail to capture the full local and global character of
signals. Examples of deficiencies are presented, and possible solutions that utilize special …

Because most real-world signals, including speech, sonar, communication, and biological
signals, are non-stationary, traditional signal analysis tools such as Fourier transforms are of …

Many of the most powerful and effective algorithms in signal processing start with the
assumption of stationarity. In addition, the deterministic portion of the signal is often …

Mixed time-frequency representations are transformations of time-varying signals that depict
how the spectral content of a signal is changing with time. They are multidimensional …

Having established the basic signal formulations in the first chapter, we now turn to the
problem of representing signals in a joint time-frequency domain. Given an analytic signal z …

Abstract, The interference terms (ITs) of the Wigner distribution (WD) dramatically affect WD
analysis results and constitute a major problem in many WD applications. This tutorial …

Using the orthogonal-like Gabor expansion, the authors decompose the Wigner-Ville
distribution (WVD) to a linear combination of localized and symmetric functions WVD/sub h …

The smoothed pseudo-Wigner distribution, the Choi-Williams distribution, and the cone-
kernel representation are three time-frequency representations (TFRs) which feature an …

pproximately 200 years ago, Fourier carried out his work on heat flow that culminated in
1811 in his celebrated memoir, where he claimed that any function of a variable, whether …