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Proceedings Paper

From the DFT to wavelet transforms
Author(s): Mark J. T. Smith
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Paper Abstract

The DFT has a long history as a powerful tool for addressing signal processing challenges. Similarly, time frequency representation like the short-time Fourier transform have been explored extensively for processing signals whose properties change with time. More recently there has been tremendous interest in applying wavelets and filter banks to signal processing problems. This paper is intended as a high level overview of filter banks and wavelets and their relationships to the traditional discrete Fourier and short-time Fourier transforms. An extensive set of references are provided to assist the interested reader in learning more about this exciting field.

Paper Details

Date Published: 17 April 2006
PDF: 8 pages
Proc. SPIE 6247, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks IV, 624702 (17 April 2006); doi: 10.1117/12.686319
Show Author Affiliations
Mark J. T. Smith, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 6247:
Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks IV
Harold H. Szu, Editor(s)

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