CAJ | 학술논문

基于支持向量机核函数的条件，将Sobolev Hilbert空间的再生核函数和多项式核函数进行有效的线性组合，给出一种新的支持向量机的组合核函数，提出一种基于再生核的组合核函数支持向量机的模式分析方法，该方法兼具了全局核函数与局部核函数的优点，且算法的复杂度被降低。仿真实验结果表明：支持向量机的核函数采用基于再生核的组合核函数是可行的，且此核函数不仅具有核函数的非线性映射特征，而且也继承了核函数对非线性逐级精细逼近的特征，模式分析的效果比单核函数可以更加细腻。
기우지지향량궤핵함수적조건，장Sobolev Hilbert공간적재생핵함수화다항식핵함수진행유효적선성조합，급출일충신적지지향량궤적조합핵함수，제출일충기우재생핵적조합핵함수지지향량궤적모식분석방법，해방법겸구료전국핵함수여국부핵함수적우점，차산법적복잡도피강저。방진실험결과표명：지지향량궤적핵함수채용기우재생핵적조합핵함수시가행적，차차핵함수불부구유핵함수적비선성영사특정，이차야계승료핵함수대비선성축급정세핍근적특정，모식분석적효과비단핵함수가이경가세니。
Based on the conditions of kernel function of Support Vector Machine(SVM), the reproducing kernel function on the Sobolev Hilbert space and polynomial kernel function are combined efficiently. A new combined kernel function is given, and a model analysis method of combined kernel SVM based on reproducing kernel is proposed, which has the advantages of global kernel function and local kernel function, and the complexity of the algorithm is reduced. The simulation results show that the kernel function of SVM adopts combined kernel function which is based on the reproducing kernel is feasible. The kernel func-tion not only has the nonlinear mapping characteristics, but also inherits good approximation of reproducing kernel function on the nonlinear characteristics step by step. The model analysis results are more delicate than individual kernels function.