Time-frequency and time-scale characterisation of the beat-by-beat high-resolution electrocardiogram

Proceedings of the Sixth Portuguese Conference on Bioemedical Engineering faro, PortugalTime-Frequency and Time-Scale distributions of sequential ST segments the High-Resolution Electrocardiogram, are represented using both the Morlet Wavelet based scalogram and the Zhao-Atlas-Marks representation. Resolution and representation readability, concerning the Ventricular Late Potentials are compared. The beat-tobeat variation of one VLP case is examined

Fixed and data adaptive kernels in Cohen's class of time-frequency distributions

Estimating the spectra of non-stationary signals represents a difficult challenge. Classical techniques employing the Fourier transform and local stationarity have been employed with limited success. A more promising approach is the use of time-frequency distributions. The majority of useful distributions have been unified under Cohen's class of distributions, a bilinear transformation with an arbitrary, fixed kernel function. The properties of several popular distributions developed from Cohen's class of distribution are examined. the ability of the kernel to suppress spurious cross-terms resulting from the bilinear nature of these distributions is examined along with their characteristics. Distributions employing a fixed kernel usually give good results only for a small class of signals. A data adaptive kernel is also examined which promises to give superior results for a broad class of signals. Results are shown for several test cases employing synthetic, analytic signals.http://archive.org/details/fixeddataadaptiv00parkLieutenant, United States NavyApproved for public release; distribution is unlimited

Time-frequency methods for coherent spectroscopy

Time-frequency decomposition techniques, borrowed from the signal-processing field, have been adapted and applied to the analysis of 2D oscillating signals. While the Fourier-analysis techniques available so far are able to interpret the information content of the oscillating signal only in terms of its frequency components, the time-frequency transforms (TFT) proposed in this work can instead provide simultaneously frequency and time resolution, unveiling the dynamics of the relevant beating components, and supplying a valuable help in their interpretation. In order to fully exploit the potentiality of this method, several TFTs have been tested in the analysis of sample 2D data. Possible artifacts and sources of misinterpretation have been identified and discussed

Interception Algorithm of S-cubed Signal Model in Stealth Radar Equipment

AbstractRadar equipment of stealth platforms such as aircraft have adopted the newest modern technology to design the signal waveforms. One of the important and effective methods is the hybrid waveform called spread spectrum stretch (S-cubed) which combines linear frequency modulation (LFM) and discrete phase code. In order to investigate the function of enemy's stealth radar equipment, the interception algorithm of S-cubed is needed. In this paper, a novel detection and parameter estimation approach for the reconnaissance S-cubed radar signal is presented. First, the generalized time-frequency representation of Zhao, Atlas, and Marks (ZAM-GTFR) and Hough transforms (HT) are applied to detecting the signal, and then the initial frequency and modulation slope of LFM are estimated from the ZAM-GTFR. On the basis of LFM information, the reconstructing signal is generated. Finally, the code rate of discrete phase code is extracted from the negative peaks of the ZAM-GTFR. Simulation results show that the proposed algorithm has higher estimation accuracy when the signal to noise ratio (SNR) is above 3 dB