Treffer: Mutual information and topology 1: Asymmetric neural network

Title:
Mutual information and topology 1: Asymmetric neural network
Contributors:
UAM. Departamento de Ingeniería Informática, Neurocomputación Biológica (ING EPS-005)
Publisher Information:
Springer Berlin Heidelberg
Publication Year:
2015
Collection:
Universidad Autónoma de Madrid (UAM): Biblos-e Archivo
Document Type:
Konferenz conference object
File Description:
application/pdf
Language:
English
Relation:
Lecture Notes in Computer Science; http://dx.doi.org/10.1007/978-3-540-28647-9_3; August 19-21, 2004; Dalian (China); International Symposium on Neural Networks, ISNN 2004; http://hdl.handle.net/10486/664567; 14; 19; 3173
DOI:
10.1007/978-3-540-28647-9_3
Rights:
© Springer-Verlag Berlin Heidelberg 2004 ; openAccess
Accession Number:
edsbas.19F7AED5
Database:
BASE

Weitere Informationen

Proceedings of International Symposium on Neural Networks, Dalian, China, August 2004 ; The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-540-28647-9_3 ; An infinite range neural network works as an associative memory device if both the learning storage and attractor abilities are large enough. This work deals with the search of an optimal topology, varying the (small-world) parameters: the average connectivity γ ranges from the fully linked to a extremely diluted network; the randomness ω ranges from purely neighbor links to a completely random network. The network capacity is measured by the mutual information, MI, between patterns and retrieval states. It is found that MI is optimized at a certain value γ o for a given 0 < ω< 1 if the network is asymmetric. ; Supported by MCyT-Spain BFI-2003-07276 and TIC 2002-572-C02