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Firstly, the approach formulates a cost functional to turn the inverse problem into a constrained minimization problem according to least squares criterion, then the resulting constrained minimization problem is transformed into an unconstrained minimization problem by using a penalty function technique, and then the closed Fr chet derivatives of the Lagrange function with respect to the properties are derived based on the calculus of variations, finally, one can solve the resulting problem by using any gradient-based algorithm and the finite-difference time-domain method.

该方法首先以最小二乘准则构造目标函数,将逆问题表示为约束最小化问题;接着应用罚函数法转化为无约束最小化问题;然后基于变分计算导出闭式的拉格朗日函数关于特征参数的Fr chet导数;最后借助梯度算法和时域有限差分法迭代反演德拜模型参数。

Different from the former study,the value region of projective operator in the neural network which they study was a general closed convex subset of n demensional Euclidean space and it wasn't a compact convex set in general,that is,the value region of projective operator was probably unbounded.

与以前研究投影算子的值域一般是n维欧氏空间中的紧凸子集不同,而是n维欧氏空间中未必有界的闭凸子集,同时目标函数也是一般的连续可微函数,未必为凸函数。

Different from the former study, the value region of projective operator in the neural network which they study was a general dosed convex subset of n demensional Euclidean space and it wasn' t a compact convex set in general, that is, the value region of projective operator was probably unbounded.

与以前研究投影算子的值域一般是n维欧氏空间中的紧凸子集不同,而是n维欧氏空间中未必有界的闭凸子集,同时目标函数也是一般的连续可微函数,未必为凸函数。

First, we extend the general finite element method from the function surface to the parameter function. Second, we bring this kind of method into the design of rational Bézier minimal surface. Third, we transform the problem of Dirichlet energy function into the problem of minimizing a discrete objective function.

首先推广了函数曲面中的有限元方法,进而研究如何针对参数曲面使用有限元方法,并把该方法引入到有理Bézier极小曲面造型的设计中,从而将连续的Dirichlet能量函数极小化问题,转化为一个离散形式的目标函数的极小化问题。

Using the convex set model to describe the uncertainty existed in the parts design.By adopting the physical planning method to construct discontentedness function of the uncertainty parameters.

用凸集模型描述零件设计中存在的不确定性,采用物理规划方法构造不确定性参数的不满意度函数,通过极小化不满意度函数最差值实现目标函数的稳健性,通过灵敏度分析实现约束函数的稳健性。

For function optimize, according to the character of objective function definition, can dispart as scatter function optimization and sequence function optimization.

对于函数优化这个问题,根据目标函数定义域的性质,可以分为离散函数最优化和连续函数最优化。

The uniformity degree and rank of the population are given to measure the distribution and quality of the solutions in the population based on the characteristic. Using the uniform degree of the population as objective function and the rank as the constrained condition, the bi-objective optimization problem is transformed into a single objective constrained optimization problem. The computational equations of the charge and force exerted on the particles are presented.

针对这一特点,定义了种群的均匀度和序值,来度量种群中解的分布和质量,将双目标优化问题转化为以均匀度为目标函数,序值为约束条件的单目标优化问题;设计了双目标优化问题粒子的电荷和受力的计算公式,提出了一种新的类电磁算法求解问题。

The Lexicographic method has subjective and empirical character,so a weighting coefficient is introduced by considering the importance and proportion of each individual object,the preferable result of every individual object can be confirmed by comparing the degree of similarity between the perfect one and the ecumenic one and the Fuzzy optimization will be perfect.

多目标最优化问题最早的出现[1],应追溯到1772年,当时franklin就提出了多目标矛盾如何协调的问题。由于多目标优化的特点,只有很少问题具有满足所有目标函数最优化的&最优解&,而大多数情况只有一个折衷意义的&偏好解[&2,3]。

The closed-characteristic expression is proven to be of a A-class entire function and some related propositions are also given. Based on them a series of nathematic deviations are done, which brings an analytic expression between the controller parameters and the cost funtion as well as the restrictions on the optimization problem. In this way the original proposition is concretized for solving.

从系统的传递函数出发,首先证明系统闭环特征函数为A-类整函数的性质并给出其它有关定理,然后进行一系列数学推导,得出了控制器参数与目标函数间的解析关系式及优化的约束条件,由此产生参数优化的具体命题。

For the global priority and infinitely splittable cases,we show that starting from an empty configuration,the solution after any one round of best responses is of a constant-factor approximation.

本文分为以下三个方面:首先,我们考虑线性拥塞博弈,对总体加权延迟函数、用户延迟和函数、资源延迟和函数等三种系统目标函数,分别给出了稳定率的上界。

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