The learning of the network is also studied and an adaptive parallel learning algorithm is proposed.

并对该神经网络模型的学习算法进行了研究，提出了一种自适应并行学习算法。

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This paper applies parallel tangents of nonlinear programming during the weights training of neural network and puts forward a neural network in view of fast learning algorithm.

因此，作者将非线性规划的平行切线算法用于神经网络的权值学习，提出了一种具有快速学习算法的神经网络。

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In order to extend common incremental learning algorithms into a parallel computation setting, an incremental learning algorithm with multiple support vector machine classifiers is proposed.

为了将一般增量学习算法扩展到并行计算环境中，提出一种基于多支持向量机分类器的增量学习算法。

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