离散时间细胞神经网络的全局学习算法

Proceedings of the Third IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-94) Pub Date : 1994-12-18 DOI:10.1109/CNNA.1994.381690

H. Magnussen, J. Nossek

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引用次数: 14

摘要

提出了离散时间细胞神经网络(DTCNNs)的两种学习算法，它们不需要网络输出轨迹的先验知识。定义了一个代价函数，并通过直接搜索优化方法和模拟退火方法使其最小化。

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Global learning algorithms for discrete-time cellular neural networks

Two learning algorithms for discrete-time cellular neural networks (DTCNNs) are proposed, which do not require the a priori knowledge of the output trajectory of the network. A cost function is defined, which is minimized by direct search optimization methods and simulated annealing.<>

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Proceedings of the Third IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-94)

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