细胞神经网络中的自组织:与Kohonen自组织图的比较

1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI:10.1109/CNNA.1998.685332

Patrick Thiran

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引用次数: 3

摘要

常微分方程(ODE)方法很难用于分析Kohonen算法的自组织。给出了两种随机自组织算法，其对应的ODE是一个CNN方程。它们的收敛与Kohonen自组织过程具有相似的特征。

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Self-organization in cellular neural networks: a comparison with Kohonen's self-organizing maps

The ordinary differential equation (ODE) method is difficult to use for analyzing the self-organization of the Kohonen algorithm. Two stochastic, 'self-organizing' algorithms, whose corresponding ODE is a CNN equation, are presented. Their convergence shares similar features with the Kohonen self-organizing process.

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1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)

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