The synchronous BEG neural network with variable dilution
Disordered Systems and Neural Networks
2007-05-23 v1
Abstract
The 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.
Cite
@article{arxiv.cond-mat/0505326,
title = {The synchronous BEG neural network with variable dilution},
author = {D. Bollé and J. Busquets Blanco},
journal= {arXiv preprint arXiv:cond-mat/0505326},
year = {2007}
}
Comments
10 pages in Latex, 15 postscript figures