IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis 

About: IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis is an academic conference. The conference publishes majorly in the area(s): Wavelet & Wavelet transform. Over the lifetime, 597 publications have been published by the conference receiving 4910 citations.

Electric power quality disturbance detection using wavelet transform analysis

Abstract: The objective of the paper is to present a novel approach to detect and localize various electric power quality disturbances using wavelet transform analysis. Unlike other approaches where the detection is performed directly in the time domain, detection using wavelet transform analysis approach is carried out in the time-scale domain. As far as detection in power quality disturbance is concerned, one- or two-scale signal decomposition is adequate to discriminate disturbances from their background. This approach is robust in detecting and localizing a wide range of power disturbances such as fast voltage fluctuations, short and long duration voltage variations, and harmonic distortion. >

Ambiguity function for a bistatic radar

Abstract: An analysis of the ambiguity function for bistatic radar is presented. Radar measurements of a moving target are considered. The effect of bistatic geometry is discussed in detail. An example is provided to illustrate the nature of ambiguity function for a variety of system configurations. >

Analysis of wavelet-domain Wiener filters

Abstract: We investigate Wiener filtering of wavelet coefficients for signal denoising Empirically designed wavelet-domain Wiener filters outperform many other denoising algorithms based on wavelet thresholding However, up to now, it has not been clear how to choose the signal model used to design the filter, because the effect of model selection on the filter performance is difficult to understand By analyzing the error involved in the Wiener filter designed with an empirically obtained signal model, we show that hard thresholding is typically outperformed by a Wiener filter designed in an alternate wavelet domain Our analysis furthermore provides a method for selecting the various parameters involved in a wavelet-domain Wiener filtering scheme

Multiple window time-frequency analysis

Abstract: We propose a robust method for estimating the time-varying spectrum of a non-stationary random process. Our approach extends Thomson's powerful multiple window spectrum estimation scheme to the time-frequency and time-scale planes. The method refines previous extensions of Thomson's method through optimally concentrated window and wavelet functions and a statistical test for extracting chirping line components.

Analysis of sound signals with high resolution matching pursuit

Abstract: Sound recordings include transients and sustained parts. Their analysis with a basis expansion is not rich enough to represent efficiently all such components. Pursuit algorithms choose the decomposition vectors depending upon the signal properties. The dictionary among which these vectors are selected is much larger than a basis. Matching pursuit is fast to compute, but can provide coarse representations. Basis pursuit gives a better representation but is very expensive in terms of calculation time. This paper develops a high resolution matching pursuit: it is a fast, high time-resolution, time-frequency analysis algorithm, that makes it likely to be used far musical applications.