Times Varying Spectral Coherence Investigation of Cardiovascular Signals Based on Energy Concentration in Healthy Young and Elderly Subjects by the Adaptive Continuous Morlet Wavelet Transform

IRBM ◽  
2018 ◽  
Vol 39 (1) ◽  
pp. 54-68 ◽  
Author(s):  
R.S. Singh ◽  
B.S. Saini ◽  
R.K. Sunkaria
1998 ◽  
Vol 30 (1-2) ◽  
pp. 131-132
Author(s):  
S. Slobounovl ◽  
R. Tutwiler ◽  
E. Slobounova

2016 ◽  
Vol 12 (S328) ◽  
pp. 230-232
Author(s):  
Adriane M. de Souza ◽  
Ezequiel Echer ◽  
Mauricio J. A. Bolzam ◽  
Markus Fränz

AbstractWavelet analysis was employed to identify the major frequencies of low-frequency waves present in the Martian magnetosheath. The Morlet wavelet transform was selected and applied to the electron density data, obtained from the Analyzer of Space Plasmas and Energetic Atoms experiment (ASPERA-3), onboard the Mars Express (MEX) spacecraft. We have selected magnetosheath crossings and analyzed electron density data. From a preliminary study of 502 magnetosheath crossings (observed during the year of 2005), we have found 1409 periods between 0.005 and 0.06Hz. The major frequencies observed were in the range 0.005-0.02 Hz with 58.5% of the 1409 frequencies identified.


2011 ◽  
Vol 474-476 ◽  
pp. 639-644 ◽  
Author(s):  
Hui Li

A new approach to bearing fault diagnosis under run-up based on order tracking and continuous complex Morlet wavelet transform demodulation technique is presented. The non-stationary vibration signal is first transformed from the time domain transient signal to angle domain stationary one using order tracking technique. Then the continuous complex Morlet wavelet transform is applied to the angle domain re-sampled signal and the complex Morlet wavelet transform based multi-scale envelope spectrum is obtained. The experimental result shows that order tracking and complex Morlet wavelet transform based multi-scale envelope spectrum can effectively diagnosis bearing localized fault.


Author(s):  
Hua Yi ◽  
Peichang Ouyang ◽  
Tao Yu ◽  
Tao Zhang

Continuous wavelet transform (CWT) is a linear convolution of signal and wavelet function for a fixed scale. This paper studies the algorithm of CWT with Morlet wavelet as mother wavelet by using nonzero-padded linear convolution. The time domain filter, which is a non-causal filter, is the sample of wavelet function. By making generalized discrete Fourier transform (GDFT) and inverse transform for this filter, we can get a geometrically weighted periodic extension of the filter when evaluated outside its original support. From this extension of the time domain filter, we can get a causal filter. In this paper, GDFT-based algorithm for CWT, which has a more concise form than that of linear convolution proposed by Jorge Martinez, is constructed by using this causal filter. The analytic expression of the GDFT of this filter, which is essential for GDFT-based algorithm for CWT, is deduced in this paper. The numerical experiments show that the calculation results of GDFT-based algorithm are stable and reliable; the running speed of GDFT-based algorithm is faster than that of the other two algorithms studied in our previous work.


Sign in / Sign up

Export Citation Format

Share Document