- 更多网络例句与相对极大点相关的网络例句 [注：此内容来源于网络，仅供参考]
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Describes general methods of point and interval parameter estimation and the small and large sample properties of estimators: method of moments, maximum likelihood, unbiased estimation, Rao-Blackwell and Lehmann-Scheffe theorems, information inequality, asymptotic relative efficiency of estimators.
点估计和区间估计的一般方法，估计量的小样本和大样本性质：矩法，极大似然估计，无偏估计，Rao-Blackwell 和 Lehmann-Scheffe 理论，信息不等式，渐进相对有效估计量。
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Maximum likelihood, unbiased estimation, Rao-Blackwell and Lehmann-Scheffe theorems, information inequality, asymptotic relative efficiency of estimators.
点估计和区间估计的一般方法，估计量的小样本和大样本性质：矩法，极大似然估计，无偏估计，Rao-Blackwell 和Lehmann-Scheffe 理论，信息不等式，渐进相对有效估计量。
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Firstly, the generalization of Fan-Ha section theorem and a general vector variational inequality without convexity assumption and minimax theorem of vector-valued function are obtained. Then, the quasi-montone vector variational inequality problem is concerned. Cx-quasi-monotone operator is defined in topological vector space, inner point of a closed convex set K is introduced, the relation between inner point and relative algebraic interior point is given, an existence result for quasi-monotone vector variational inequality is obtained.
第三章主要研究了向量变分不等式和极小极大定理(来源：3282AB83C论文网www.abclunwen.com)，建立了广义的Fan-Ha截口定理、新的向量变分不等式与极小极大定理，并在拓扑向量空间中定义了C_x-拟单调算子，引入了闭凸集K的inner点，给出了inner点与相对代数内点的关系，利用innK_c代替K的拓扑内部，建立了新的拟单调向量变分不等式。
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The question of searching characteristic points or straight lines on moving rigid body is decomposed into two relatively independent sub-questions. The first one is to evaluate the characteristic of points and straight lines on moving rigid body, whose mathematics model is a kind of special non-differential max-mini optimal problem with inequality constraints. By the method of Saddle-point Programming and maximum entropy, the problem can be transformed as a differential optimal problem with single objective. The second oner is to search approximative character points or straight lines on moving rigid body within design space, whose mathematic model is nonlinear and non-differential problem with multiple constraints.
本文将在运动刚体上寻找特征点或直线的优化问题分解为两个相对独立的子问题，一是对运动刚体上点或直线的特征性评定，其实质是平面曲线的圆度或直线度的评定问题，优化模型是以最大误差为最小作为优化目标的约束不可微的优化问题，本文采用鞍点规划和极大熵方法，将其转化为单目标可微优化模型；二是在设计空间内，寻找运动刚体上特征性评定指标最小的近似特征点或直线，其优化模型是非线性、多约束的不可微优化问题，本文提出用遗传算法和BFGS局部搜索法相结合来求解。
- 更多网络解释与相对极大点相关的网络解释 [注：此内容来源于网络，仅供参考]
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position function：位置函数
position 位置 | position function 位置函数 | position of a relative maximum 相对极大点
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position of a relative maximum：相对极大点
position function 位置函数 | position of a relative maximum 相对极大点 | position of an extremum 极值点
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position of an extremum：极值点
position of a relative maximum 相对极大点 | position of an extremum 极值点 | position parameter 位置参数