Abstract
A Hopfield neural network was constructed with relevance to protein dynamics. The dynamics of this network was analyzed by determining the distribution of first passage times between memories and its dependence on temperature. The distribution depended on the updating scheme. This illustrates the importance of choosing an updating scheme that leads to physically meaningful results in computational models of dynamic processes, such as in neural networks or molecular dynamics.
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Liebovitch, L.S., Zochowski, M. Significance of Updating Schemes in Computational Models: Dynamics of Neutral Networks. Journal of Statistical Physics 90, 253–260 (1998). https://doi.org/10.1023/A:1023259903363
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DOI: https://doi.org/10.1023/A:1023259903363