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。

BP neural network based on sensitivity analysis is used as base classifier to learn the subsets and redundant genes are further removed.

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从故障反应能力、对各类故障的灵敏度以及采用多模量时检测故障的冗余度等方面对各变换阵进行了分析比较。

Analysis and comparisons are made for those transformations according to the sensitivity and redundancy to all types of fault.

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