1) subdifferential
次微分
1.
Optimal conditions of set-valued maps optimization with subdifferential;
次微分意义下集值映射优化问题的最优性条件
2.
The Henig Efficient Subdifferential of Set-valued Mapping and Stability;
集值映射的Henig有效次微分及其稳定性
3.
The stability of strictly efficient points of set-valued optimization problem in the sense of subdifferential;
集值优化问题严有效点集的次微分稳定性
3) Quadratic differential
二次微分
1.
Using the method of quadratic differential,we obtain that the Affine transformation in angle region is not an extremal mapping with its boundary values,and give explicitly an unique extremal Teichmller mapping with the same boundary values as the Affine transformation.
采用二次微分的方法，得到了角形区域Ω１的Ａｆｆｉｎｅ变换关于其边界值不是极值映照。
4) 1.5-Differential
1.5次微分
1.
1.5-Differential cathodic stripping voltammetric determination of trace selenium in water;
1.5次微分阴极溶出伏安法测定水样中痕量硒(Ⅳ)
5) order differential
3.5次微分
6) γ-subdifferential
γ-次微分
1.
A kind of set-valued differential(γ-subdifferential) of functionals in normed linear space was defined,and its properties and application to nonsmooth multiobjective programming problem was discussed,so that some new results were obtained.
定义了赋范线性空间上泛函的一种新型集值导数(γ-次微分),讨论了它的一些性质及其在非光滑数学规划问题上的一些应用,得到了一些新的结果,这些结果改进和推广了已有的相关结论,对于进一步研究此问题提供了可靠的理论依据。
2.
By means of γ-subdifferential and γ-convexity some results on maximum entropy method for γ-convex programming are introduced.
利用γ－次微分和γ－凸性的概念，给出了一类γ－凸规划极大熵方法的几个结果：（１）如果ｘ是γ－凸规划的严格局部最优解，那么ｘ也是它的唯一最优解；（２）设ｘｐ是问题：ｍｉｎｆ（ｘ），ｘ∈Ωｐ｛ｘ｜ｇｐ（ｘ）≤０｝的严格局部有限最优解，ｘ是问题ｍｉｎｆ（ｘ），ｘ∈Ω＝｛ｘ｜ｇｉ（ｘ）≤０，ｉ＝１，…，ｍ｝的严格局部有限最优解，如果ｘ∈ｂｄΩ，那么ｇｐ（ｘｐ）＝０；（３）设ｘ∈ｂｄΩ，如果ｘｐ和ｘ同（２），那么ｘｐ→ｘ，ｐ→∞。
补充资料：次微分
次微分
subdifferential
次微分阵由山场，图血l;cy6及一帅epe。”“幼] 定义在与空间Y对偶的空间X上的凸函数f:X卜R在点x。的次微分是Y中由下式定义的点集: 刁f(x‘、)={夕EY二f(x)一f(x。)) )
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