Based on the sensitivity of neural network of system identification, a method of descending neural network sensitivity in control systems is proposed in this paper.
基于系统辨识的神经网络灵敏度，提出了降低用于控制系统中神经网络灵敏度的一种方法。
BP neural network based on sensitivity analysis is used as base classifier to learn the subsets and redundant genes are further removed.
采用基于灵敏度分析的BP神经网络模型作为基分类器，进一步剔除冗余基因。
In addition, rough sets is high sensitivity to the noise in the decision table, this weakness can be counterbalance by BP neural network.
同时，粗糙集对于决策表噪声比较敏感，BP神经网络可以克服这个缺点。
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