We consider a family of models, which generalizes the Hopfield model of neural networks, and can be solved likewise. This family contains palimpsestic schemes, which give memories that behave in a similar way as a working (short-term) memory. The replica method leads to a simple formalism ...
Hopfield, J. J. Neural networks and physical systems with emergent collective computational abilities. Proc. Natl. Acad. Sci. USA 79, 2554–2558 (1982). Article CAS Google Scholar Amit, D. J. & Brunel, N. Learning internal representations in an attractor neural network with analogue neurons...
Mechanisms of persistent activity in cortical circuits: possible neural substrates for working memory. Annu Rev Neurosci , 2017 ,: 603 -627 Google Scholar [16] Hopfield J J. Neural networks and physical systems with emergent collective computational abilities. Proc Natl Acad Sci USA , 1982...
firstly, artificial neural network are briefly introduced the characteristics, working principle, neuron model. Secondly, the Hopfield neural network algorithm were discussed, a detailed analysis of the two kinds of Hopfield neural network (discrete Hopfield neural network and continuous Hopfield neural[tra...
Transformer Excitation Inrush Current Recognition in Coal Mine Based on Hopfield Neural Network In order to solve problem that differential transformer inrush current protection in some coals make fault movement,the paper from transformer inrush and i... MM Huang,LI Chen-Chen,XU Wei,... - 《Co...
The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists.
aThe proposed algorithm employs a continuous Hopfield network for optimizing the prediction error,resulting in a dynamical system that,under suitable assumptions,converges towards the parameter values. 提出的算法使用一个连续的Hopfield网络为优选预言错误,造成,在适当的假定外,聚合往参数值的一个动力学系统。[...