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Proceedings Paper

Spectral approach to classification based on generalized unconditional tests
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Paper Abstract

Spectral approach to distribution-free classification is presented. The discriminant function is based on generalized unconditional tests. The main steps of the algorithms are: (1) finding a set of deadlock generalized tests, (2) computing a local discriminant function for each such a test, and (3) performing the actual classification of the observed pattern into a class. The spectral algorithms involve computation of the Walsh and Reed-Muller (conjunctive) spectra using fast algorithms.

Paper Details

Date Published: 21 April 1995
PDF: 10 pages
Proc. SPIE 2501, Visual Communications and Image Processing '95, (21 April 1995); doi: 10.1117/12.206660
Show Author Affiliations
Karen O. Egiazarian, Tampere Univ. of Technology (Finland)
Jaakko T. Astola, Tampere Univ. of Technology (Finland)
Sos S. Agaian, Tufts Univ. (United States)


Published in SPIE Proceedings Vol. 2501:
Visual Communications and Image Processing '95
Lance T. Wu, Editor(s)

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