针对文本中事件专题挖掘，提出事件模型学习算法。

For text-mining method of event topic, the method of event model was also proposed.

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本文从神经网络模型的结构出发，对学习算法提出了一系列改进和优化措施，以加快网络的学习速度，并增加模型的稳定性。

With the study of neural network model, this paper advances some of improvement and optimization techniques that can accelerate the learning speed of network and increase the stability of model.

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提出基于TDNN神经网络的线性噪声消除器，讨论了它的模型与学习算法及其通用逼近性。

Linear noise canceller based on TDNN was proposed, and its model, learning algorithm and universal approximation were discussed.

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