本文建立了具有正核的多维卷积算子逼近的量化定理。
In this paper, the quantitative theorems on the approximation by multidimensional convolution operators are established.
以原始条件属性集为起点并结合算子，通过向属性核的递减式逼近，得到属性的最小相对约简。
Acquiring optimal relative reduction by descending approach to core of attribute from original set of conditional attribute and combining with operator.
应用LOO估算选择的核函数模型能够较好地逼近最佳值。
The kernel function model selected by LOO estimation can approach the best value satisfactorily.
应用推荐