1) complex PCA
复线性判别
2) linear discriminant
线性判别
1.
Applying the linear discriminant approach to the intermediate-term patterns of seismic chains, we present an approach to find the precursors of large earthquakes.
将线性判别方法应用于地震链的中期图象,给出一种探索大地震前兆的途径。
2.
This paper uses the relationship of regression analysis and discriminant analysis to apply the method of influence analysis of regression analysis in discriminant analysis to discuss the influence of a set data to the precision of a sample linear discriminant function.
利用判别分析与回归分析的关系，将回归分析中影响分析的方法应用到判别分析中，讨论了一组试验数据对样本线性判别函数精度的影响问题。
3) Fisher linear discriminant
Fisher线性判别
1.
Relative energy attached to each subspace was calculated as eigenvalue and feature dimension reduction was conducted by Fisher linear discriminant analysis.
针对表面肌电信号的分类问题,采用最佳小波包分解构造最能体现分类能力的小波包基,用Fisher线性判别分析对肌电信号各个子空间的相对能量特征进行降维处理,然后利用BP神经网络进行分类识别。
2.
The method uses a self-organizing map to obtain the class label for each training sample and enhanced Fisher linear discriminant(EFM) to find the optimal projection for pattern classification,and a Gaussian distribution to model the class-conditional density function of the projected samples for each class.
该方法首先使用自组织映射网络为每个训练样本确立类别标签 ,然后用改进的 Fisher线性判别模型对所有样本进行投影以尽可能拉大各类之间的距离 ,最后使用高斯分布对每类样本进行建模 。
3.
Finally,PCA and Fisher linear discriminant are used to reduce the dimensiona-lity and optimize discriminative classification respectively.
寻求有效且分类性能高的人脸表征方法至关重要,在局部二值模式(LBP)的纹理提取基础上,引进一种改进的新型的局部三值模式(LTP)纹理特征提取方法,此方法对光照变化和噪声更加鲁棒且更有利于分类,最后采用PCA和Fisher线性判别分析对特征空间进行降维和最优鉴别分类。
6) Fisher linear discriminant analysis
Fisher线性判别
1.
The FFC method, which is robust to changes in illumination,applies the Fisher linear discriminant analysis to an augmented force-field feature vector derived from the fo.
该方法通过力场图像转换提取耳廓图像特征后,采用Fisher线性判别分类识别,减小了光照变化对耳廓识别的影响。
补充资料：复线
有两组或两组以上轨道的铁道或电车道，相对方向的车辆可以同时通行（区别于‘单线’）。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条