Thermodynamic properties of extremely diluted symmetric Q-Ising neural networks

Using the replica-symmetric mean-field theory approach the thermodynamic and. retrieval properties of extremely diluted symmetric Q-Ising neural networks are studied. In particular, capacity-gain parameter and capacity-temperature phase diagrams are derived for Q = 3, 4 and infinity. The zero-temperature results are compared with those obtained from a study of the dynamics of the model. Furthermore, the de Almeida-Thouless line is determined. Where appropriate, the difference from other Q-Ising architectures is outlined.