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zeroes of Bergman kernel function Bergman核函数的零点
Bergman kernel functions Bergman核函数
Bergman kernel function Bergman核函数
Theoretically how to choose Kernel function remains unsolved. 在理论上，怎样选择核函数，还是一个未解决的问题。
We first answer two open problems of Boas. Furthermore, we prove the stability theorem of the Bergman kernel for various non-smooth pseudoconvex domains. 我们回答了Boas提出的两个open problem更进一步我们证明了大量非光滑边界拟凸域上稳定性定理成立。
Thus, the Bergman kernel functionis K((w,z);(w,z)) = Jdet(Jf)j2K((w~,0);(w*,0)), where (.Jj) is the Jacobi matrix off,det(Jf) is the determinant of (Jr). 这样，其Bergman核函数K((w，z);(w，z))=|det(J_f)|~2K((w~*，O);(w~*，O))，这里（J_f）表示变换f的雅可比矩阵，det（J_f）表示（J_f）的行列式。
Super advertising shield and attached a crucial handoff IE kernel function. 附带超强的广告屏蔽和IE内核一键切换功能。
This chapter describes where in the Linux kernel sources you should start looking for particular kernel functions. 本章主要描叙寻找某个特殊核心函数时用到的Linux核心资源。
Most of the kernel functions are polynomial for curve & surface modelling in CAGD. 在计算机辅助几何设计中 ,曲线曲面拟合一般采用多项式作为基函数。
However, computing kernel uncorrelated vectors is computationally expensive due to the utilization of kernel functions. 然而，由于核函数的运用，计算核不相关矢量集变得更加复杂。
Applications use kernel functions through application programming interfaces (API),which are a set of standard routines used by programs. 应用程序通过应用程序编程接口（API）使用内核的功能，API是一组由程序使用的标准例行程序。
Kernel function is applied in PCA and DDA, so the linear discriminance method is dislinearized. 在主分量分析方法以及线性判别式方法中,引入核函数,使得原来的线性判别方法非线性化。
For this reason, several important properties of kernel function are discussed on the basis of support vector machine. 为此，在研究支持向量机的基础上，给出了核函数的若干重要性质。
Applications use kernel functions through application programming interfaces (API), which are a set of standard routines used by programs. 应用程序通过应用程序编程接口（api）使用内核的功能，api是一组由程序使用的标准例行程序。
The kernel function is modified by means of a conformal mapping, which makes the kernel function data-dependent. 利用与数据有关的保角映射，使核函数具有数据依赖性。
When the Gaussian kernel function width is 2.0, RVM method possesses more perfect prediction performance. 当高斯核函数的宽度值取为2.;0时，相关向量机方法具有较为理想的预测效果。
The comparison of different kernel functions for SVM shows that RBF kernel function is most suitable for recognition of maize disease. 不同分类核函数的相互比较分析表明，径向基核函数最适合于玉米病害的分类识别。
The results indicate that the AUC value is closely related with the kernel functions and multi-class transformation metho. 实验结果表明,AUC值和核函数和多类转换方法的选取都有着密切的联系。
The kernel function can be unit hydrograph of deterministic system or time series model of stochastic system. 通常核心函数可为定率系统之单位历线或序率系统之时间序列模式。
Geological information at different depth was described by introducing a mixed window kernel function to SVM. 通过引入窗口核函数，准确地反映了不同深度的地质信息。