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线性阈值神经元网络的循环动力学分析

Analysis of cyclic dynamics for networks of linear threshold neurons.

作者信息

Tang H J, Tan K C, Zhang Weinian

机构信息

Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576.

出版信息

Neural Comput. 2005 Jan;17(1):97-114. doi: 10.1162/0899766052530820.

Abstract

The network of neurons with linear threshold (LT) transfer functions is a prominent model to emulate the behavior of cortical neurons. The analysis of dynamic properties for LT networks has attracted growing interest, such as multistability and boundedness. However, not much is known about how the connection strength and external inputs are related to oscillatory behaviors. Periodic oscillation is an important characteristic that relates to nondivergence, which shows that the network is still bounded although unstable modes exist. By concentrating on a general parameterized two-cell network, theoretical results for geometrical properties and existence of periodic orbits are presented. Although it is restricted to two-dimensional systems, the analysis can provide a useful contribution to analyze cyclic dynamics of some specific LT networks of high dimension. As an application, it is extended to an important class of biologically motivated networks of large scale: the winner-take-all model using local excitation and global inhibition.

摘要

具有线性阈值(LT)传递函数的神经元网络是模拟皮层神经元行为的一个重要模型。对LT网络动态特性的分析引起了越来越多的关注,比如多稳定性和有界性。然而,关于连接强度和外部输入如何与振荡行为相关,目前所知甚少。周期性振荡是一个与非发散相关的重要特征,这表明尽管存在不稳定模式,但网络仍然是有界的。通过专注于一个一般的参数化双细胞网络,给出了关于几何性质和周期轨道存在性的理论结果。虽然它仅限于二维系统,但该分析可为分析某些特定高维LT网络的循环动力学提供有益的贡献。作为一个应用,它被扩展到一类重要的具有生物学动机的大规模网络:使用局部兴奋和全局抑制的胜者全得模型。

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