Thermodynamic properties of extremely diluted symmetric Q-Ising neural networks

Details Thermodynamic properties of extremely diluted symmetric Q-Ising neural networks Thermodynamic properties of extremely diluted symmetric Q-Ising neural networks

2000-02-14

arxiv.org/abs/cond-mat/0002200v2

J.Phys.A: Math.Gen. 33, 6481-6495 (2000).

Physics

Condensed Matter

Disordered Systems and Neural Networks

16 pages Latex including 6 eps-figures. Corrections, also in most of the figures have been made

Scientific paper

10.1088/0305-4470/33/37/302

Using the replica-symmetric mean-field theory approach the thermodynamic and retrieval properties of extremely diluted {\it symmetric} $Q$-Ising neural networks are studied. In particular, capacity-gain parameter and capacity-temperature phase diagrams are derived for $Q=3, 4$ and $Q=\infty$. 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 with other $Q$-Ising architectures is outlined.

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