Retrieval properties of diluted attractor neural networks
Camilo Rodrigues Neto, José F. Fontanari · Journal of Physics A Mathematical and General · 1996
We investigate the dependence of the retrieval properties of the pseudo-inverse and optimal attractor neural networks on the fraction of stored patterns , the temperature T and the margin parameter . Phase diagrams in the full space of parameters are presented in the regime of extreme dilution, i.e. when the connectivity C satisfies the condition , where N is the number of neurons. Furthermore, we study analytically the neighbourhood of a stored pattern for both models by calculating the average fraction of unstable sites in a pattern that differs by d sites from a given stored pattern. This analysis may shed light on the properties of the basins of attraction of the stored patterns.