提出了基于非线性主元分析(NLPCA)网络和概率神经网络( )的故障诊断方法.首先使用非线性主元分析神经网络进行特征提取,降低数据维数,既简化了诊断过程,又确保了故障...
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根据超声多普勒血流信号和血管壁搏动信号的统计特性，提出了一种基于主元分析的非线性滤波方法。
A nonlinear filtering method based on principle component analysis (PCA) was proposed according to the statistical characteristics of the Doppler ultrasound blood flow signal and wall thump signal.
在训练阶段，核-主元分析用来捕捉非线性的手写变化。
In the training phase, kernel principal component analysis is used to capture nonlinear handwriting variations.
对27个主方支圆间隙K型相贯节点进行了非线性有限元分析。
Nonlinear finite element analysis, including 27 gap K-joints with square and circular hollow sections, has been carried out.
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