On the local frequency, group shift, and cross-terms in some multidimensional time-frequency distributions: a method for multidimensional time-frequency analysis

1995 ◽  
Vol 43 (7) ◽  
pp. 1719-1724 ◽  
Author(s):  
S. Stankovic ◽  
L. Stankovic ◽  
Z. Uskokovic
Keyword(s):  
Frequency Analysis ◽  
Time Frequency Analysis ◽  
Frequency Distributions ◽  
Time Frequency ◽  
Frequency Group ◽  
Cross Terms ◽  
Group Shift

scholarly journals Time-Frequency Analysis of Clinical Percussion Signals Using Matrix Pencil Method

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Moinuddin Bhuiyan ◽  
Eugene V. Malyarenko ◽  
Mircea A. Pantea ◽  
Dante Capaldi ◽  
Alfred E. Baylor ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Matrix Pencil ◽  
Time Frequency Analysis ◽  
Frequency Distributions ◽  
Practical Applications ◽  
Time Frequency ◽  
Matrix Pencil Method ◽  
Oscillation Modes ◽  
Cross Terms ◽  
Time Frequency Localization

This paper discusses time-frequency analysis of clinical percussion signals produced by tapping over human chest or abdomen with a neurological hammer and recorded with an air microphone. The analysis of short, highly damped percussion signals using conventional time-frequency distributions (TFDs) meets certain difficulties, such as poor time-frequency localization, cross terms, and masking of the lower energy features by the higher energy ones. The above shortcomings lead to inaccurate and ambiguous representation of the signal behavior in the time-frequency plane. This work describes an attempt to construct a TF representation specifically tailored to clinical percussion signals to achieve better resolution of individual components corresponding to physical oscillation modes. Matrix Pencil Method (MPM) is used to decompose the signal into a set of exponentially damped sinusoids, which are then plotted in the time-frequency plane. Such representation provides better visualization of the signal structure than the commonly used frequency-amplitude plots and facilitates tracking subtle changes in the signal for diagnostic purposes. The performance of our approach has been verified on both ideal and real percussion signals. The MPM-based time-frequency analysis appears to be a better choice for clinical percussion signals than conventional TFDs, while its ability to visualize damping has immediate practical applications.

Time–frequency analysis in infant cry classification using quadratic time frequency distributions

2018 ◽  
Vol 38 (3) ◽  
pp. 634-645
Author(s):  
J. Saraswathy ◽  
M. Hariharan ◽  
Wan Khairunizam ◽  
J. Sarojini ◽  
N. Thiyagar ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Time Frequency Analysis ◽  
Frequency Distributions ◽  
Infant Cry ◽  
Time Frequency

Contrast of Time-Frequency Analysis Methods and Fusion of Wigner-Ville Distribution and Wavelet Transform

2013 ◽  
Vol 805-806 ◽  
pp. 1962-1965 ◽  
Author(s):  
Hui Xing Zhang ◽  
Jie Li ◽  
Qi Lin ◽  
Jian Zhi Qu ◽  
Qi Zheng Yang
Keyword(s):  
Wavelet Transform ◽  
Frequency Analysis ◽  
New Method ◽  
Frequency Resolution ◽  
Time Frequency Analysis ◽  
Frequency Distributions ◽  
Time Frequency ◽  
Synthetic Signal ◽  
Analysis Methods ◽  
Stationary Signals

Time-frequency analysis is a powerful tool for analyzing non-stationary signals, which can describe the signals frequency varying with time and provide us the joint information of time domain and frequency domain of the signal. We use a synthetic signal to realize the time-frequency analysis methods of wavelet transform, S transform and Wigner-Ville distribution. Through comparing and analyzing those time-frequency distributions, we propose a new method of integrating wavelet transform and Wigner-Ville distribution. This new method gives a better result than that of wavelet transform and Wigner-Ville distribution and increases the time-frequency resolution.

Time-Frequency Analysis of Partial Discharge Phenomena in SF6 gas using Wavelet Transform

1997 ◽  
Vol 117 (3) ◽  
pp. 338-345 ◽  
Author(s):  
Masatake Kawada ◽  
Masakazu Wada ◽  
Zen-Ichiro Kawasaki ◽  
Kenji Matsu-ura ◽  
Makoto Kawasaki
Keyword(s):  
Wavelet Transform ◽  
Frequency Analysis ◽  
Partial Discharge ◽  
Time Frequency Analysis ◽  
Time Frequency
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