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Proceedings Paper

Signal quantization and the optimization of digital filters
Author(s): Pertti T. Koivisto; Heikki Huttunen; Pauli Kuosmanen; Jaakko T. Astola
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Paper Abstract

Filters can be designed using a pair of training signals, a desired one and a corrupted one, by finding from a filter class the filter that maps the corrupted training signal closest to the desired signal. This paper addresses the effect that the wordlength used in the training signals has on the applicability of the found optimal filters to other signals with different wordlength. The study is done by concentrating on three filter classes that are shown to reveal different aspects of the topic in hand.

Paper Details

Date Published: 25 March 1996
PDF: 12 pages
Proc. SPIE 2662, Nonlinear Image Processing VII, (25 March 1996); doi: 10.1117/12.235817
Show Author Affiliations
Pertti T. Koivisto, Tampere Univ. of Technology (Finland)
Heikki Huttunen, Tampere Univ. of Technology (Finland)
Pauli Kuosmanen, Tampere Univ. of Technology (Finland)
Jaakko T. Astola, Tampere Univ. of Technology (Finland)

Published in SPIE Proceedings Vol. 2662:
Nonlinear Image Processing VII
Edward R. Dougherty; Jaakko T. Astola; Harold G. Longbotham, Editor(s)

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