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Proceedings Paper

Redundancy reduction as the basis for visual signal processing
Author(s): A. Norman Redlich
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Paper Abstract

An environmentally driven, self-organizing principle for encoding sensory messages is proposed, based on the need to learn their statistical properties. Optimal encodings are found for two cases: First, for linear maps the optimal transformation eliminates pairwise correlations between input `pixels.' This solution is applied to predict the retinal transform based on the autocorrelator for natural scenes. Second, when the input `images' consist of a set of weakly coupled, local `bound states,' then a series of non-linear maps is found which optimally segments the input. This is demonstrated by using it to efficiently learn, without supervision, the statistics of English text.

Paper Details

Date Published: 1 July 1992
PDF: 10 pages
Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); doi: 10.1117/12.140085
Show Author Affiliations
A. Norman Redlich, Institute for Advanced Study (United States)

Published in SPIE Proceedings Vol. 1710:
Science of Artificial Neural Networks
Dennis W. Ruck, Editor(s)

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