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摘要

我们研究了基于可表示为常微分方程的受控二维系统的神经网络的某些方面:使用二维动力系统的渐近行为进行优化设计,以及使用二维受控系统的最优控制来设计学习策略。
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Neural networks in 2-D continuous time
We examine certain aspects of neural networks based on controlled 2D systems representable as ordinary differential equations: the use of the asymptotic behaviour of 2D dynamical systems for optimal design, and the use of optimal control of 2D controlled systems for devising learning strategies.
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