In engineering, digital signal processing techniques need to be carefully selected according to the characteristics of the signals of interest. The frequency-based and time-frequency techniques have been frequently mentioned in some literature (Cohen, 1995). The frequencybased techniques (FBTs) have been widely used for stationary signal analysis. For nonstationary signals, the time-frequency t...

Short Time Fourier Transform (STFT) is an important technique for the time-frequency analysis of a time varying signal. The basic approach behind it involves the application of a Fast Fourier Transform (FFT) to a signal multiplied with an appropriate window function with fixed resolution. The selection of an appropriate window size is difficult when no background information about the input sig...

For micromotion scatterers with small rotating radii, the micro-Doppler (m-D) effect interferes with cross-range compression in inverse synthetic aperture radar (ISAR) imaging and leads to a blurred main body image. In this paper, a novel method is proposed to remove the m-D effect by promoting the joint sparsity in the time-frequency domain. Firstly, to obtain the time-frequency representation...

Various time-frequency methods have been used to study time-varying properties of non-stationary neurophysiological signals. In the present study, a time-frequency coherence estimate using continuous wavelet transform (CWT) together with its confidence intervals are proposed to evaluate the correlation between two non-stationary processes. The approach is based on averaging over repeat trials. ...

In 1995-1996 the Acoustic Thermometry of Ocean Climate (ATOC) experiment provided an opportunity to study long-range broadband transmissions over a series of months using mode-resolving vertical arrays. A 75-Hz source off the California coast transmitted broadband pulses to receiving arrays in the North Pacific, located at ranges of 3515 and 5171 km. This paper develops a short-time Fourier tra...

Electroencephalography (EEG) is widely used in clinical settings to investigate neuropathology. Since EEG signals contain a wealth of information about brain functions, there are many approaches to analyzing EEG signals with spectral techniques. In this study, the short-time Fourier transform (STFT) and wavelet transform (WT) were applied to EEG signals obtained from a normal child and from a c...

Shoulder musculoskeletal disorders are among the most prevalent work-related musculoskeletal disorders and constitute an important health problem. One of the occupations that are most affected is workers on assembly lines (Leclerc et al., 2004), as these jobs requires repetitive movement, which, as a risk factor, has been found positively associated with shoulder disorders. Repetitive movement ...

A time-frequency analysis, which represents the time change of a signal, is significant in all fields. Wigner distribution, a short time Fourier transform (STFT), a kernel method, and a characteristic function method etc. are known as a time-frequency analyzing method, and those methods have merits and demerits. STFT method has been used as ultrasound blood-flow imaging for a long time, because...

Audio sources frequently concentrate much of their energy into a relatively small proportion of the available time-frequency cells in a short-time Fourier transform (STFT). This sparsity makes it possible to separate sources, to some degree, simply by selecting STFT cells dominated by the desired source, setting all others to zero (or to an estimate of the obscured target value), and inverting ...

This research paper presents some methods to assess the performance of Wigner Ville Distribution for Time-Frequency representation of non-stationary signals, in comparison with the other representations like STFT, Spectrogram etc. The simultaneous timefrequency resolution of WVD is one of the important properties which makes it preferable for analysis and detection of linear FM and transient si...