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Proceedings Paper

Using chaotic neural nets to compress, store, and transmit information
Author(s): Gianfranco Basti; Antonio Luigi Perrone; Paola Cocciolo
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Paper Abstract

In order to find a very efficient technique to compress, store, and transmit to earth information from a satellite we developed a scheme of chaotic neural net using a new technique of extraction of unstable orbits within a chaotic attractor without applying classical embedding dimensions. We illustrate this technique both from the theoretical and the experimental standpoint. From the theoretical standpoint we show that by this extraction technique it is possible to perform a series expansion of a chaotic dynamics directly through all its composing cycles. Finally, we show how to apply these new possibilities deriving from our new technique of chaos detection, characterization, and stabilization to design a chaotic neural net. Because it is possible to profit by all the skeleton of unstable periodic orbits (i.e., all the inner frequencies) characterizing a chaotic attractor to store information, this net can in principle display an exponential increasing of memory capacity with respect to classical attractor nets.

Paper Details

Date Published: 2 March 1994
PDF: 14 pages
Proc. SPIE 2243, Applications of Artificial Neural Networks V, (2 March 1994); doi: 10.1117/12.169996
Show Author Affiliations
Gianfranco Basti, Pontifical Gregorian Univ., INFN, and INO (Italy)
Antonio Luigi Perrone, Univ. di Roma Tor Vergata, INFN, and INO (Italy)
Paola Cocciolo, Univ. di Roma Tor Vergata (Italy)

Published in SPIE Proceedings Vol. 2243:
Applications of Artificial Neural Networks V
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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