Title
Periodic Wavelet Transforms and Periodicity Detection
Abstract
The theory of periodic wavelet transforms presented here was originally developed to deal with the problem of epileptic seizure prediction. A central theorem in the theory is the characterization of wavelets having time and scale periodic wavelet transforms. In fact, we prove that such wavelets are precisely generalized Haar wavelets plus a logarithmic term. It became apparent that the aforementioned theorem could not only be quantified to analyze seizure prediction, but could also provide a technique to address a large class of periodicity detection problems. An essential step in this quantification is the geometric and linear algebra construction of a generalized Haar wavelet associated with a given periodicity. This gives rise to an algorithm for peri- odicity detection based on the periodicity of wavelet transforms defined by generalized Haar wavelets and implemented by wavelet averaging methods. The algorithm detects periodicities embedded in significant noise. The algorithm depends on a discretized version Wp ˆf(n;m) of the continuous wavelet transform. The version defined provides a fast algorithm with which to compute Wp ˆf(n;m) from W p ˆf(n¡1;m) or Wp ˆf(n;m ¡ 1). This has led to the theory of non-dyadic wavelet frames in l 2( ) developed by the second-named author, and which will appear elsewhere.
Year
DOI
Venue
2002
10.1137/S0036139900379638
SIAM Journal of Applied Mathematics
Keywords
Field
DocType
optimal generalized haar wavelets,epileptic seizure prediction,continuous wavelet transform,periodicity detection algorithm,wavelet frames on .,linear algebra,wavelet transform
Mathematical optimization,Lifting scheme,Gabor wavelet,Mathematical analysis,Legendre wavelet,Discrete wavelet transform,Haar wavelet,Cascade algorithm,Wavelet packet decomposition,Mathematics,Wavelet
Journal
Volume
Issue
Citations 
62
4
2
PageRank 
References 
Authors
0.38
2
2
Name
Order
Citations
PageRank
Götz E. Pfander120.38
John J. Benedetto213216.90