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Mean-field theory of vector spin models on networks with arbitrary degree distributions

Fernando L Metz and Thomas Peron
Journal of Physics: Complexity 3 (1) 015008 (2022)
https://doi.org/10.1088/2632-072X/ac4bed

Feed-forward chains of recurrent attractor neural networks with finite dilution near saturation

F.L. Metz and W.K. Theumann
Physica A: Statistical Mechanics and its Applications 368 (1) 273 (2006)
https://doi.org/10.1016/j.physa.2005.11.049

Synchronous versus sequential updating in the three-state Ising neural network with variable dilution

D. Bollé, R. Erichsen and T. Verbeiren
Physica A: Statistical Mechanics and its Applications 368 (2) 311 (2006)
https://doi.org/10.1016/j.physa.2005.12.052

The Blume-Emery-Griffiths neural network with synchronous updating and variable dilution

D. Bollé and J. Busquets Blanco
The European Physical Journal B 47 (2) 281 (2005)
https://doi.org/10.1140/epjb/e2005-00328-7

Analytic solution of attractor neural networks on scale-free graphs

I Pérez Castillo, B Wemmenhove, J P L Hatchett, et al.
Journal of Physics A: Mathematical and General 37 (37) 8789 (2004)
https://doi.org/10.1088/0305-4470/37/37/002

Thermodynamic properties of extremely diluted symmetricQ-Ising neural networks

D Bollé, D M Carlucci and G M Shim
Journal of Physics A: Mathematical and General 33 (37) 6481 (2000)
https://doi.org/10.1088/0305-4470/33/37/302

Statistical mechanics of a Hopfield neural-network model in a transverse field

Yu-qiang Ma, Yue-ming Zhang, Yu-gang Ma and Chang-de Gong
Physical Review E 47 (6) 3985 (1993)
https://doi.org/10.1103/PhysRevE.47.3985