1) weighted main-part modulus
加权主部光滑模
2) weighted moduli of smoothness
加权光滑模
1.
A new weighted moduli of smoothness w~2_(φ~λ)(f,t)_w and a new Jocabi weighted w(x)=(x~(-a)(1+αx)~b)(0≤a<1,b>0) are studied,generalized Baskakov operator is introduced and the pointwise results of weighted approximation is obtained.
引用新的加权光滑模w2φλ(f,t)w和新的Jocabi权函数w(x)=x-a(1+αx)b(0≤a<1,b≥0),研究了广义Baskakov算子,得出了其加权逼近的点态结果,进一步统一和补充了以前的结果。
2.
In this paper, we make use of a new weighted moduli of smoothness w2(?)λ (f, t)w to give a pointwise estimate of weighted simultaneous approximation by Bernstein operator with Jacobi weight.
本文给出了Bernstein算子加权同时逼近的点态估计,在此使用的是Jacobi权函数ω(x)=x~a(1-x)~b(0≤a,b<1,a,b不全为零),引入新的加权光滑模ω_(■λ)~2(f,t)_ω,是对以前结果的补充和完善。
3.
The equivalence relation between the weighted K-functional and the weighted moduli of smoothness in Lψ spaces is studied.
研究Lψ空间上的加权K-泛函与加权光滑模之间的等价性,为在Lψ空间上建立线性算子的加权逼近提供一个有力工具。
3) weighted modulus of smoothness
加权D-T光滑模
4) Local Adaptive Weights Smoothing
局部自适应加权平滑
1.
The paper aims to present an efficient and feasible method, which integrates the Independent Component Analysis, Local Adaptive Weights Smoothing and Generalized Hyperbolic Distribution, to solve the problem.
本文的主要目的是将独立成分分析、局部自适应加权平滑法、广义双曲分布结合起来,解决高维投资组合风险度量的问题,并将其应用于中国证券市场的实证分析,度量风险,并寻找最优投资组合策略。
5) weighting amoothing
加权平滑
6) exponent weighted gliding average model
指数加权平滑模型
1.
The exponent weighted gliding average model is improved to fit in with the forecasting of the parameters with various changing law.
对指数加权平滑模型进行了改进,使之能适用于多种不同变化规律的参数的预报。
补充资料：主部
1.主管的部门。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条