Analysis of Wavelet Transform Multiscale Products for Step Detection and Estimation

Author(s):  
Brian M. Sadler ◽  
Ananthram Swami
Author(s):  
MARCELA MORVIDONE

A new approach for joint detection and estimation of signals embedded in stationary random noise is considered and compared to previously studied methods, for the subclass of amplitude and frequency modulated signals. The method is a "reassigned" version of the Hough-wavelet transform and it is compared to the matched filter approach and the Hough-wavelet transform itself. Extensions to previous results obtained with these two methods are also presented. As target application, the problem of gravitational waves at interferometric detectors is considered. Our main conclusion is that there is no gain in introducing the reassignment operation.


1997 ◽  
Vol 34 (2) ◽  
pp. 73-75 ◽  
Author(s):  
Christian R. Mittermayr ◽  
Erwin Rosenberg ◽  
Manfred Grasserbauer

1997 ◽  
Vol 36 (04/05) ◽  
pp. 356-359 ◽  
Author(s):  
M. Sekine ◽  
M. Ogawa ◽  
T. Togawa ◽  
Y. Fukui ◽  
T. Tamura

Abstract:In this study we have attempted to classify the acceleration signal, while walking both at horizontal level, and upstairs and downstairs, using wavelet analysis. The acceleration signal close to the body’s center of gravity was measured while the subjects walked in a corridor and up and down a stairway. The data for four steps were analyzed and the Daubecies 3 wavelet transform was applied to the sequential data. The variables to be discriminated were the waveforms related to levels -4 and -5. The sum of the square values at each step was compared at levels -4 and -5. Downstairs walking could be discriminated from other types of walking, showing the largest value for level -5. Walking at horizontal level was compared with upstairs walking for level -4. It was possible to discriminate the continuous dynamic responses to walking by the wavelet transform.


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