运用非线性主成分分析法对欧亚地区1948—2007年冬季海平面气压距平场进行分析。
Eurasian winter sea level pressure anomalies during 1948-2007 were investigated by applying a nonlinear principal component analysis (NLPCA) method.
运用非线性主成分分析法对欧亚地区1948—2007年冬季海平面气压距平场进行分析。
Eurasian summer sea level pressure anomalies during 1948 -2007 were investigated by applying a Nonlinear Principal Component Analysis (NLPCA) method.
基于核主成分分析（KPCA）的人脸识别算法能够提取非线性图像特征，在小样本训练条件下有较好性能。
The algorithm of face recognition based on kernel principal component analysis(KPCA)can abstract nonlinear features of image and can get better performance under less sample training conditions.
论文中重点介绍了该种方法的降维思想，以及用主成分分析方法、对应分析方法和非线性映射方法解决问题的步骤。
In this paper, the emphasis is placed on the technique for reducing the dimensions. The principal analysis, correspondence analysis and nonlinear mapping are described in detail.
针对减速箱运行状态和特征参数之间存在的复杂非线性关系，提出了基于主成分分析的RBF神经网络减速箱运行状态诊断方法。
As to the complicated nonlinear relation existing between running status of gear reducer and characteristic parameters, PCA-based RBF neural network reducer running status diagnostics is put forward.
仿真实验结果表明，主曲线成分分析能很好地解决非线性主成分问题，应用前景广阔。
Experimental results show that principal curve component analysis is excellent for solving nonlinear principal component problem, and it has great applications potentials.
主成分分析方法主要利用数据的线性相关性来降维，并不适合非线性相关的情况。
As principal component analysis mainly use the linear correlation of the data, we propose a nonlinear principal component analysis method, by combining the mercer kernel function with it.
主成分分析方法主要利用数据的线性相关性来降维，并不适合非线性相关的情况。
As principal component analysis mainly use the linear correlation of the data, we propose a nonlinear principal component analysis method, by combining the mercer kernel function with it.
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