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Proceedings Paper

Improved linear discrimination using time-frequency dictionaries
Author(s): Jonathan B. Buckheit; David L. Donoho
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Paper Abstract

We consider linear discriminant analysis in the setting where the objects (signals/images) have many dimensions (samples/pixels) and there are relatively few training samples. We discuss ways that time frequency dictionaries can be used to adaptively select a small set of derived features which lead to improved misclassification rates.

Paper Details

Date Published: 1 September 1995
PDF: 12 pages
Proc. SPIE 2569, Wavelet Applications in Signal and Image Processing III, (1 September 1995); doi: 10.1117/12.217608
Show Author Affiliations
Jonathan B. Buckheit, Stanford Univ. (United States)
David L. Donoho, Stanford Univ. (United States)


Published in SPIE Proceedings Vol. 2569:
Wavelet Applications in Signal and Image Processing III
Andrew F. Laine; Michael A. Unser, Editor(s)

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