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Proceedings Paper

More results on orthogonal wavelets with optimum time-frequency resolution
Author(s): Joel M. Morris; Vinod Akunuri; Hui Xie
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Paper Abstract

Signal decomposition techniques are an important tool for analyzing nonstationary signals. The proper selection of time-frequency basis functions for the decomposition is essential to a variety of signal processing applications. The discrete wavelet transform (DWT) is increasingly being used for signal analysis, but not until recently has attention been paid to the time-frequency resolution property of wavelets. This paper describes additional results on our procedure to design wavelets with better time-frequency resolution. In particular, our optimal duration-bandwidth product wavelets (ODBW) have better duration-bandwidth product, as a function of wavelet-defining filter length N, than Daubechies' minimum phase and least- asymmetric wavelets, and Dorize and Villemoes' optimum wavelets over the range N equals 8 to 64. Some examples and comparisons with these traditional wavelets are presented.

Paper Details

Date Published: 6 April 1995
PDF: 11 pages
Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); doi: 10.1117/12.205426
Show Author Affiliations
Joel M. Morris, Univ. of Maryland/Baltimore County (United States)
Vinod Akunuri, Univ. of Maryland/Baltimore County (United States)
Hui Xie, Univ. of Maryland/Baltimore County (United States)


Published in SPIE Proceedings Vol. 2491:
Wavelet Applications II
Harold H. Szu, Editor(s)

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