The synchronous BEG neural network with variable dilution

dc.creatorBollé, D.
dc.creatorBlanco, J. Busquets
dc.date2005-05-12
dc.date.accessioned2026-07-25T15:51:32Z
dc.descriptionThe thermodynamic and retrieval properties of the Blume-Emery-Griffiths neural network with synchronous updating and variable dilution are studied using replica mean-field theory. Several forms of dilution are allowed by pruning the different types of couplings present in the Hamiltonian. The appearance and properties of two-cycles are discussed. Capacity-temperature phase diagrams are derived for several values of the pattern activity. The results are compared with those for sequential updating. The effect of self-coupling is studied. Furthermore, the optimal combination of dilution parameters giving the largest critical capacity is obtained.
dc.description10 pages in Latex, 15 postscript figures
dc.identifierhttps://arxiv.org/abs/cond-mat/0505326
dc.identifierhttp://arxiv.org/abs/cond-mat/0505326
dc.identifier.urihttps://dspace.dare.co.zw/handle/123456789/37561
dc.subjectDisordered Systems and Neural Networks
dc.titleThe synchronous BEG neural network with variable dilution
dc.typetext

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