摘要
By means of the theory of spline functions in Hilbert space, multivariate polynomial natural splines smoothing of scattered data are constructed without boundary conditions on certain bounded domains in R as a generalization of the well known uniariate natural polynomial splines smoothing. Generalized Cross-validation as a useful method for choosing a good ridge parameter of these multivariate smoothing splines is discussed. We give a available algorithm. Especialy an algorithm for bicubic splines smoothing is fairly easy to implement as example, and should be very useful in multivariate numerical analysis and signal analysis.
By means of the theory of spline functions in Hilbert space, multivariate polynomial natural splines smoothing of scattered data are constructed without boundary conditions on certain bounded domains in R as a generalization of the well known uniariate natural polynomial splines smoothing. Generalized Cross-validation as a useful method for choosing a good ridge parameter of these multivariate smoothing splines is discussed. We give a available algorithm. Especialy an algorithm for bicubic splines smoothing is fairly easy to implement as example, and should be very useful in multivariate numerical analysis and signal analysis.
出处
《计算数学》
CSCD
北大核心
1998年第4期383-392,共10页
Mathematica Numerica Sinica
基金
国家自然科学基金!19571091
中山大学高等学术研究中心基金!97M7
