Feature extraction based on kernel function and application of improved methods
一种基于核函数特征提取改进方法的应用

For the standard KCCA method in the case of training samples increases the complexity of the corresponding surge in the computer memory occupied by a large quantity of defects,based on the standard derivation of KCCA feature extraction methods,this paper proposed an improved feature extraction method of nuclear function.In this method,the value based on characteristics of the training sample size to judge the degree of importance,and then completed the corresponding eigenvectors,and combined with the SVDD c...