The storage capacity of Potts models for semantic memory retrieval

DOI10.1088/1742-5468/2005/08/P08010zbMath1456.82853arXivcond-mat/0507111OpenAlexW3100753476MaRDI QIDQ4968872

Emilio Kropff, Alessandro Treves

Publication date: 9 July 2019

Published in: Journal of Statistical Mechanics: Theory and Experiment (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/cond-mat/0507111

zbMATH Keywords

spin glasses (theory)neuronal networks (theory)

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Statistical mechanics of random media, disordered materials (including liquid crystals and spin glasses) (82D30) Neural nets applied to problems in time-dependent statistical mechanics (82C32) Dynamics of disordered systems (random Ising systems, etc.) in time-dependent statistical mechanics (82C44)

Related Items (4)

The complexity of latching transitions in large scale cortical networks ⋮ Storing structured sparse memories in a multi-modular cortical network model ⋮ Reducing a cortical network to a Potts model yields storage capacity estimates ⋮ Gibbs measures of Potts model on Cayley trees: A survey and applications

Cites Work

• An associative network with spatially organized connectivity
• Modeling Brain Function
• Short- and long-range connections in autoassociative memory
• Mean-field theory for the Q-state Potts-glass neural network with biased patterns

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