Time evolution of the extremely diluted Blume-Emery-Griffiths neural network
Entity
UAM. Departamento de Ingeniería InformáticaPublisher
American Physical SocietyDate
2003-12-17Citation
10.1103/PhysRevE.68.062901
Physical Review E 68.6 (2003): 062901
ISSN
1550-2376 (online); 1539-3755 (print)DOI
10.1103/PhysRevE.68.062901Funded by
One of the authors (D.B.) wants to thank T. Verbeiren and J. Busquets Blanco for critical discussions and the Fund for Scientific Research–Flanders, Belgium for financial support. D.R.C.D. acknowledges a Ramón y Cajal grant from the Spanish Ministry of Science (MCyT), and thanks the K.U. of Leuven, Belgium, for a visiting grant. E.K. warmly thanks for hospitality the Abdus Salam International Center for Theoretica Physics, Trieste, and is financially supported by Grant No. DGI (MCyT) BFM 2001-291-C02-01. The work of W.K.T. was partially supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil, and the same author acknowledges the Fundacão de Amparo à Pesquisa do Estado de Rio Grande do Sul (FAPERGS), Brazil for a visiting scientist grant to the IFUFRGS.Editor's Version
http://dx.doi.org/10.1103/PhysRevE.68.062901Subjects
InformáticaRights
© 2003 American Physical SocietyAbstract
A study of the time evolution and a stability analysis of the phases in the extremely diluted Blume-Emery-
Griffiths neural network model are shown to yield new phase diagrams in which fluctuation retrieval may drive
pattern retrieval. It is shown that saddle-point solutions associated with fluctuation overlaps slow down the
flow of the network states towards the retrieval fixed points. A comparison of the performance with other
three-state networks is also presented.
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Google Scholar:Bollé, D.
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Domínguez Carreta, David Renato
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Erichsen, R.
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Korutcheva, Elka
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Theumann, W. K.
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