A learning algorithm based on a hard limiter for feedforward neural networks (NN) is presented, and is applied in solving classification problems on separable convex sets and disjoint sets.
提出了基于硬限幅功能函数的前向神经网络的分类学习算法，并将其应用于可分凸集或不交集合的分类。
A learning algorithm based on a hard limiter for feedforward neural networks (NN) is presented, and is applied in solving classification problems on separable convex sets and disjoint sets.
提出了基于硬限幅功能函数的前向神经网络的分类学习算法，并将其应用于可分凸集或不交集合的分类。
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