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Cited article:

The Blume–Emery–Griffiths neural network: dynamics for arbitrary temperature

D. Bollé, J.Busquets Blanco, G.M. Shim and T. Verbeiren
Physica A: Statistical Mechanics and its Applications 331 (1-2) 319 (2004)
https://doi.org/10.1016/S0378-4371(03)00629-0

The signal-to-noise analysis of the Little–Hopfield model revisited

D Bollé, J Busquets Blanco and T Verbeiren
Journal of Physics A: Mathematical and General 37 (6) 1951 (2004)
https://doi.org/10.1088/0305-4470/37/6/001

Dynamics of Ising random-bond models: neural network and random-anisotropy-axis model

D R C Dominguez and W K Theumann
Journal of Physics A: Mathematical and General 28 (1) 63 (1995)
https://doi.org/10.1088/0305-4470/28/1/013

Retrieval and chaos in layeredQ-Ising neural networks

D. Bollé, G. M. Shim and B. Vinck
Journal of Statistical Physics 74 (3-4) 583 (1994)
https://doi.org/10.1007/BF02188572

A probabilistic approach to parallel dynamics for the Little-Hopfield model

A E Patrick and V A Zagrebnov
Journal of Physics A: Mathematical and General 24 (14) 3413 (1991)
https://doi.org/10.1088/0305-4470/24/14/028

On the parallel dynamics for the Little-Hopfield model

A. E. Patrick and V. A. Zagrebnov
Journal of Statistical Physics 63 (1-2) 59 (1991)
https://doi.org/10.1007/BF01026592