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Analog Neural Networks as Decoders

Erlanson, Ruth and Abu-Mostafa, Yaser (1991) Analog Neural Networks as Decoders. In: Advances in Neural Information Processing Systems 3. Morgan Kaufmann , San Mateo, CA, pp. 585-588. ISBN 1-55860-184-8. https://resolver.caltech.edu/CaltechAUTHORS:20160119-162724779

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Abstract

Analog neural networks with feedback can be used to implement l(Winner-Take-All (KWTA) networks. In turn, KWTA networks can be used as decoders of a class of nonlinear error-correcting codes. By interconnecting such KWTA networks, we can construct decoders capable of decoding more powerful codes. We consider several families of interconnected KWTA networks, analyze their performance in terms of coding theory metrics, and consider the feasibility of embedding such networks in VLSI technologies.


Item Type:Book Section
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http://papers.nips.cc/paper/399-analog-neural-networks-as-decodersOrganizationArticle
Additional Information:© 1991 Morgan Kaufmann.
Record Number:CaltechAUTHORS:20160119-162724779
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20160119-162724779
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:63783
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:20 Jan 2016 00:39
Last Modified:03 Oct 2019 09:31

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