Wavelet-based algorithm for signal analysis

Authors:
Norman C. F. Tse;L. L. Lai
Affiliations:
Division of Building Science and Technology, City University of Hong Kong, Kowloon, Hong Kong;School of Engineering and Mathematical Sciences, City University, London, UK
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2007

Citing 3
Cited 2

Multiridge detection and time-frequency reconstruction

IEEE Transactions on Signal Processing
Characterization of signals by the ridges of their wavelettransforms

IEEE Transactions on Signal Processing
Computational Signal Processing with Wavelets

Computational Signal Processing with Wavelets

A New Matrix Method for Reconstruction of Band-Limited Periodic Signals from the Sets of Integrated Values

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Wavelet ridges for musical instrument classification

Journal of Intelligent Information Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a computational algorithm for identifying power frequency variations and integer harmonics by using wavelet-based transform. The continuous wavelet transform (CWT) using the complex Morlet wavelet (CMW) is adopted to detect the harmonics presented in a power signal. A frequency detection algorithm is developed from the wavelet scalogram and ridges. A necessary condition is established to discriminate adjacent frequencies. The instantaneous frequency identification approach is applied to determine the frequencies components. An algorithm based on the discrete stationary wavelet transform (DSWT) is adopted to denoise the wavelet ridges. Experimental work has been used to demonstrate the superiority of this approach as compared to the more conventional one such as the fast Fourier transform.