摘要
《核选择和非线性特征提取的双线性分析》一文提出了一种新颖的核Fisher准则FKC,并用迭代分析算法FKA求得最优解,但其迭代收敛性缺乏理论上的证明。从理论上对FKA算法的迭代收敛性进行了分析和探讨,并运用Radermacher复杂性分析法进行证明。
In the paper ＂bilinear analysis for kernel selection and nonlinear feature extraction＂ （IEEE Trans on NN, 2007, 18 （5））, the authors presented a unified criterion, Fisher and Kernel Criterion （FKC）, for feature extraction and recognition and used an iterative procedure to optimize the new criterion. But there is still no theoretical discussion concerning the convergence issue of such an iterative procedure. An iterative convergence analysis of Fisher and Kernel analysis algorithm（FKA） is povided using the concept of Radermacher complexity.
出处
《计算机工程与应用》
CSCD
2012年第34期40-44,共5页
Computer Engineering and Applications
基金
国家自然科学基金资助项目(No.60773206
No.60704047)
