Thermodynamic properties of fully connected Q-Ising neural networks
D. Bollé, Heiko Rieger, G. M. Shim · Journal of Physics A Mathematical and General · 1994
The thermodynamic and retrieval properties of fully connected Q-Ising networks are studied in the replica-symmetric mean-field approximation. In particular, capacity-gain parameter and capacity-temperature phase diagrams are derived for Q=3, 4 and Q= infinity and different distributions of the stored patterns. Furthermore, the optimal gain function is determined in order to obtain the best performance. Where appropriate, the results are compared with the diluted and layered versions of these models.