Heart sounds and murmurs are timevarying signals that would best be analyzed using timefrequency analysis. Windowed Wigner-Ville distribution (WWVD) and smooth windowed Wigner-Vffle distribution (SWWVD) are used to obtain the timefrequency representation of the signal. Determination of parameter setting of WWVD and SWWVD will eliminate the cross-terms and improve time frequency representation. ...

We describe a coherent network algorithm for detection and reconstruction of gravitational wave bursts. The algorithm works for two and more arbitrarily aligned detectors and can be used for both all-sky and triggered burst searches. We describe the main components of the algorithm, including the timefrequency analysis in a wavelet domain, construction of the likelihood timefrequency maps, and ...

This work investigates the application of the Ensemble Empirical Mode Decomposition (EEMD) and the timefrequency techniques for treatment of the electromyography (EMG) signal. The EMG signals are usually corrupted by artifacts that hide useful information then the extraction of high-resolution EMG signals from recordings contaminated with back ground noise becomes an important problem. The Ense...

In this paper, the power quality (PQ) disturbances have been detected and classified using Stockwell’s transform (S-transform) rule-based decision tree (DT) according to IEEE standards. The proposed technique based on extracted features of PQ events signals, which are from timefrequency analysis. Several considered with simple complex include spike, flicker, oscillatory transient, impulsive not...

To overcome the limitation induced by the fixed timefrequency resolution over the whole time-frequency plane of Gabor frames, we propose a simple extension of the Gabor theory leading to the construction of frames with timefrequency resolution evolving over time or frequency. We describe the construction of such frames and give the explicit formulation of the canonical dual frame for some condi...

In this paper a method for Myoelectric signal (MES) segmentation and classification is proposed. The classical moving average technique augmented with Principal Components Analysis (PCA), and timefrequency analysis were used for segmentation. Multiresolution Wavelet Analysis (MRWA) was adopted as an effective feature extraction technique while Artificial Neural Networks (ANN) was used for MES c...

Diagnostic of machine using the timefrequency representation of vibration is becoming widely used by many companies and experts. In recent years, the preventive maintenance is no more desirable and in fact it has evolved into the prediction maintenance. The current methods of machine diagnosis can not provide detailed diagnostics and condition prediction. This paper proposes the application of ...

We address the problem of signal decomposition. We specify signal components by the property that their energies are localised and disjoint in the time-frequency plane. Rather than modelling the signal directly, we represent the timefrequency energy of the signal using a finite mixture model. This model is used to develop a partitioning of the timefrequency plane, allowing the application of ti...

The texture is very important cue in region based segmentation of images. Texture features play a very important role in computer vision and pattern recognition. Texture Applications include industrial inspection, estimation of object range and orientation, shape analysis, satellite imaging, and medical diagnosis. In this paper, we study of different definitions of texture. The timefrequency tr...

This paper investigates the performance of the T-distributions as compared to other well known time-frequency distributions in a recently proposed blind source separation algorithm based on timefrequency analysis. In this study we considered linear FM signals (chirps), non-linear FM signals, and doppler signals. Keyword:Blind Source Separation; Time-frequency representation; Doppler signal; Lin...