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Proceedings Paper

Adaptive wavelet transforms of singular and chaotic signals
Author(s): Ryan Benton; Afshin Ganjoo; Beth Lumetta; Daryl Spillman; Jason Ring
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Paper Abstract

In the field of signal processing, there is a need to quickly and efficiently detect and extract information from signals. One type of signal feature that is difficult to process is a discontinuous singularity and chaotic structure. In this paper, we conduct an experiment that employs adaptive wavelet transforms to efficiently detect signals from simulated data. The adaptive wavelet transformations create super-mother wavelets, which are used to extract a singularity signal from a noisy transmission.

Paper Details

Date Published: 22 March 1996
PDF: 8 pages
Proc. SPIE 2762, Wavelet Applications III, (22 March 1996); doi: 10.1117/12.235988
Show Author Affiliations
Ryan Benton, Univ. of Southwestern Louisiana (United States)
Afshin Ganjoo, Univ. of Southwestern Louisiana (United States)
Beth Lumetta, Univ. of Southwestern Louisiana (United States)
Daryl Spillman, Univ. of Southwestern Louisiana (United States)
Jason Ring, Univ. of Southwestern Louisiana (United States)


Published in SPIE Proceedings Vol. 2762:
Wavelet Applications III
Harold H. Szu, Editor(s)

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