As the basic unit of Neural Network, Neural Controllers with different learning rules will result in different control effects for the learning process of synaptic weights.

作为神经网络控制的基本单元，采用不同学习规则的神经元控制器，对神经元的学习过程将产生不同的影响。

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For the learning process, a new kind of empirical risk function is proposed which is differentiable and can be minimized by gradient descent strategy.

对于参数的学习，提出了一种适用于分类器的可微经验风险函数，该函数能够有效地利用梯度下降法进行最小化。

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For the learning process, a new kind of empirical risk function is proposed which is differentiable and can be minimized by gradient descent strategy.

对于参数的学习，提出了一种适用于分类器的可微经验风险函数，该函数能够有效地利用梯度下降法进行最小化。

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