在核探测器和前置放大器获取核信息及波形数字化系统将模拟核信号数字化的过程中，都不可避免地会使核信号发生畸变，影响测量结果的精度。

During the detector and preamplifier acquire nuclear information and WDS convert the analog signals to digit value, the nuclear signals will inevitable be distorted to make the final result worse.

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本文将专家在平衡—模拟倒摆小车时记录下来的数据经处理后，用监督式学习的方法训练一前置式神经网络。

In this paper, we present a method of training a feedforward neural network using supervised learning scheme to balance an inverted pendulum and cart system.

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系统硬件的模拟电路部分设计了四电极传感器前置模拟电路以及热敏电阻测温电路；

The analog circuit of the system in this thesis is composed with pre-positive circuit of 4-probe electrode sensor and temperature-measure circuit.

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