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Attractor neural networks with patchy connectivity
KTH, School of Computer Science and Communication (CSC), Numerical Analysis and Computer Science, NADA.
KTH, School of Computer Science and Communication (CSC), Numerical Analysis and Computer Science, NADA.
KTH, School of Computer Science and Communication (CSC), Numerical Analysis and Computer Science, NADA.ORCID iD: 0000-0002-2358-7815
2007 (English)In: ESANN 2005 Proceedings - 13th European Symposium on Artificial Neural Networks, 2007, 429-434 p.Conference paper, Published paper (Refereed)
Abstract [en]

We investigate the effects of patchy (clustered) connectivity in sparsely connected attractor neural networks (NNs). This study is motivated by the fact that the connectivity of pyramidal neurons in layer II/III of the mammalian visual cortex is patchy and sparse. The storage capacity of hypercolumnar attractor NNs that use the Hopfield and Willshaw learning rules with this kind of connectivity is investigated analytically as well as by simulation experiments. We find that patchy connectivity gives a higher storage capacity, given an overall sparse connectivity and regardless of learning rule.

Place, publisher, year, edition, pages
2007. 429-434 p.
Keyword [en]
Artificial intelligence, Cognitive systems
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-154667Scopus ID: 2-s2.0-84886997164ISBN: 2930307056 (print)ISBN: 978-293030705-3 OAI: oai:DiVA.org:kth-154667DiVA: diva2:758596
Conference
13th European Symposium on Artificial Neural Networks, ESANN 2005, 27 April 2005 through 29 April 2005, Bruges, Belgium
Note

QC 20141027

Available from: 2014-10-27 Created: 2014-10-27 Last updated: 2014-10-27Bibliographically approved

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Output format
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