例如，某些基本的神经网络，它们的感知器只倾向于学习线形函数(通过划一条线可以把函数输入解析到分类系统中)。

For instance, a certain kind of basic neural network, the perceptron, is biased to learning only linear functions (functions with inputs that can be separated into classifications by drawing a line).

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一个使用这个规则的神经网络称为感知器，并且这个规则被称为感知器学习规则。

A neural net that USES this rule is known as a perceptron, and this rule is called the perceptron learning rule.

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本文研究神经网络的多层感知器模型在语音识别中的应用。

This paper describes the use of multi-layer perception model of neural network in speech recognition.

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