人工神经网络中的奇异摄动和时间尺度

[1991] Proceedings of the 30th IEEE Conference on Decision and Control Pub Date : 1991-12-11 DOI:10.1109/CDC.1991.261077

K. L. Moore, D. Naidu

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引用次数: 0

摘要

在Hopfield型递归神经网络中，学习和计算过程分为慢现象和快现象。将相应的动力学方程转换成奇异摄动和时间尺度理论的框架。讨论了在求近似解时出现的退化和渐近展开问题。

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Singular perturbations and time scales in artificial neural networks

The learning and computing processes in a recursive neural network of the Hopfield type are identified as slow and fast phenomena. The corresponding dynamical equations are cast to fit into the framework of the theory of singular perturbations and time scales. The issues of degeneration and asymptotic expansions arising in obtaining approximate solutions are addressed.<>

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[1991] Proceedings of the 30th IEEE Conference on Decision and Control

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