方向导数
- 网络Directional derivative;direction derivative
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基于方向导数和B样条小波的图像边缘检测
Image edge detection based on directional derivative and cubic B-spline wavelet
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(h,φ)-凸函数的广义方向导数及其性质
Generalized Directional Derivative of ( h ;φ) - Convex Function and its Properties
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比如,在i向量的方向导数,就是x轴方向的分量。
So , for example , the directional derivative in the direction of I hat is the component along the x axes .
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考虑它的Hadamard下方向导数,给出了它的结构表达式。
The expression of its lower - Hadamard directional derivative is obtained .
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用方向导数分析JC法的误差
Analyzing the error of JC method by means of directional derivative
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Clarke广义方向导数与普通方向导数相等的一个充要条件
A Necessary and Sufficient Condition for Clarke General Directional Derivative Equals to Common Directional Derivative
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Lipschitz规划极值函数上(下)方向导数界的估计
Estimation of the bound of upper ( lower ) directional derivatives for extremal function in Lipschitz programming
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所以这个与g=c相切的导数,应该是f的方向导数,在这个方向下,应该是等于0的。
So the derivative in any direction , tangent to g equals c , should be the directional derivative of f , in any such direction , should be zero .
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然后利用正切锥方向导数定义一类正切锥F凸函数类,并给出了(VP)正切锥真有效解的充分性条件;
Then , we define a class of tangent cone F convexity in terms of the tangent cone directional derivative , and prove the sufficient optimality conditions for ( VP ) .
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本文给出了局部Lipschitz函数的Clarke广义方向导数与普通方向导数相等的一个充要条件。
A necessary and sufficient condition that Clarke general directional derivative is equals to common directional derivative for locally Lipschitz function is given in this paper .
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本文提出一种新的三维波动方程P-R分裂偏移方法,即方向导数法三维P-R分裂偏移方法。
The paper describes a new three-dimensional wave equation P-R splitting migra - tion-three-dimensional P-R splitting migration using directional derivative .
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然后,引进上、下方向导数和广义Minty型向量变分不等式,研究了问题(VP)的最优性条件。
Then , by introducing upper and lower directional derivatives and generalized Minty type vector variational inequality , the optimality conditions of the problem ( VP ) are studied .
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Haralick算法的缺点是曲面拟合系数和方向导数的方向较难确定。
The disadvantage of Haralick is the difficulty for determining the coefficients of the surface fitting and the orientation of the directional second order derivation .
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利用Hadamard方向导数这一工具,获得了不等式约束条件下多目标规划问题的约束品性,这一约束品性在某种程度上是Maeda和Preda等人研究结果的进一步推广。
In this paper , we obtain constrain qualifications of multi-object optimal programming with the Hadamard directional derivative , extend Maeda and Preda 's results to some extent .
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本文对Lipschitz规划讨论了极值作为扰动向量的函数的微分稳定性.在M&F约束准则下给出了极值函数上(下)方向导数的界。
His paper discusses the stability of differential of extremum which is a function of perturbation vector for Lipschitz programming . The bound of upper ( lower ) directional derivatives for extremal function is given under the M - F constrain criterion .
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本文我们首先给出一类向量值优化问题(VP)的正切锥真有效解的定义,在锥方向导数的假设下,讨论了一类单目标问题的最优性必要条件;
In the paper , we give the definition of the tangent cone properly efficient solution for a class of vector valued optimizations ( VP ) . Under the cone directional derivative assumption , we first discuss the optimality necessary conditions for a single objective problem .
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引入了相应于矢量场的方向导数。
The directional derivative according to the vector fields was introduced .
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锥方向导数和锥次梯度的性质及其在最优化中的应用
The Properties of the Cone Directional Derivative and Application in Optimization
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45°方程叠后深度偏移的方向导数法
Directional derivative method for 45 ° acoustic equation poststack depth migration
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基于四方向导数信息的图像非线性扩散去噪
Nonlinear Diffusion Model Based on Four Directional Derivatives for Image Denoising
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基于方向导数的多光谱图像快速融合新算法
A Novel Fast Multispectral Image Fusion Algorithm Based on Directional Derivative
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非凸二层规划的广义方向导数和广义微分
Generalized Directional Derivative and Differential of Nonconvex Two level Programming
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讨论了几种不同的方向导数和梯度的定义。
We discuss several different definitions of directional derivative and gradient vector .
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我们来用方向导数,来描述一下相同的东西。
Let 's say the same thing in terms of directional derivatives .
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一种基于方向导数的边缘直线检测算法
A Novel Edge Line Detection Method Based on Directional Derivative
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对于一般的非凸函数,其方向导数不具备任何凸性,可以利用一般正齐次函数的回收函数来给出它的一个上凸近似。
For a general convex function , directional derivative is not convex .
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多维微分、方向导数和梯度。
Derivatives in higher dimensions , directional derivative and gradient .
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基本上是的,那就是方向导数。
And that 's basically , yes , that 's the directional derivative .
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近似已知函数方向导数的误差估计
Error Estimates of Directional Derivatives of Approximately Specified Functions
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多维参数线性规划的解分割和方向导数
Partition of solutions and directional derivatives for linear programming problem with higher-dimensional parameters