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A macrodynamical approach to the analysis of neural networks

机译:宏观动力学方法的神经网络分析

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摘要

General features of an asymptotical method for an analyzingcomplex system like neural networks are presented. The method isanalogous to the mean-field approach and allows treatment not only ofsteady states but also of dynamical properties of networks. It may alsobe interpreted as a Galerkin procedure for the master equation. Thetypes of neural networks and related problems to which the method can beapplied are discussed. It is shown that the method can treatsynchronization processes, networks of excitable neurons, nonidenticalneurons, and nonidentical synapses
机译:提出了一种复杂的系统如神经网络的渐近方法的一般特征。该方法类似于均值场方法,不仅可以处理稳态,还可以处理网络的动态特性。对于主方程,也可以将其解释为Galerkin过程。讨论了神经网络的类型以及可以应用该方法的相关问题。结果表明,该方法可以治疗同步过程,兴奋性神经元网络,异同神经元和异同突触。

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