Singularity and Similarity Detection from Signals Using Wavelet Transform
Signal Processing
2021-11-04 v1
Abstract
The wavelet transform and related techniques are used to analyze singular and fractal signals. The normalized wavelet scalogram is introduced to detect singularities including jumps, cusps and other sharply changing points. The wavelet auto-covariance is applied to estimate the self-similarity exponent for statistical self-affine signals.
Keywords
Cite
@article{arxiv.2110.15825,
title = {Singularity and Similarity Detection from Signals Using Wavelet Transform},
author = {Hua-Liang Wei and S. A. Billings},
journal= {arXiv preprint arXiv:2110.15825},
year = {2021}
}
Comments
6 pages, 9 figures, 1 table