具有非线性模板的CNN动态学习算法。1 .离散时间情况

1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96) Pub Date : 1996-06-24 DOI:10.1109/CNNA.1996.566618

R. Tetzlaff, D. Wolf

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引用次数: 9

摘要

提出了一种基于梯度非线性模板的离散细胞神经网络(DTCNN)动态学习算法。为了利用DTCNN对非线性时空系统进行动力学建模，应用该算法求出网络参数。详细讨论了两种不同的非线性离散系统的结果。

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A learning algorithm for the dynamics of CNN with nonlinear templates. I. Discrete-time case

A learning algorithm for the dynamics of discrete-time cellular neural networks (DTCNN) with gradient-based nonlinear templates is presented. For modeling the dynamics of nonlinear spatio-temporal systems with DTCNN, the algorithm is applied to find the network parameters. Results for two different nonlinear discrete-time systems are discussed in detail.

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1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96)

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