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In this paper, we study characterizations of admissible in the general linear model Y, Xβ,ε|ε~(0,σ~2∑. We demonstrate that an admissible linear estimator is as the conditional generalized ridge-type estimation in the no constraint, equality constraint, inequality constraint general linear model. We study the superiority of this conditional generalized ridge-type estimation, and prove that it is superior to the restricted best linear unbiased estimator in terms of mean squares. We also give the choice of the matrix K.

本文主要研究了一般线性模型Y,Xβ,ε|ε~(0,σ~2∑中参数估计的可容许性特征,得到了一般线性模型在无约束,有等式约束及有不等式约束下,可容许线性估计均具有条件广义岭估计的形式的结论,并且讨论了这一条件广义岭估计的优良性,证明了其在均方误差和均方误差矩阵意义下都优于约束最小二乘估计,给出了参数矩阵K的选取方法。

In addition, we generalize the algorithm to solve linear constrained optimization problems and give good results.

另外将此算法推广求解线性约束优化问题,不需要将约束问题转化为无约束问题,获得了较好的实验效果。

Interval slope method is proposed for a class of unconstrained min-max-min problems, in which the objective functions are factorable functions. An interval algorithm is given by interval slope discard tests and interval extension of objective functions. Numerical results are also presented.

讨论目标函数为因子函数的离散无约束min-max-min问题,利用区间斜率,构造目标函数的区间扩张和区问斜率删除原则,建立了求解离散无约束min-max-min问题的区间斜率算法,并给出了数值算例。

To inequality constraint s, a check procedure and a penalty function procedure are proposed, and equality constraints are dealt with by a procedure of solving equations in which tear equations may be converged by an iterating way or a penalty function way.

在无约束非线性规划问题全局优化的模拟退火算法基础上,进行有约束问题求解的进一步探讨,对不等式约束条件提出了检验法和罚函数法的处理方法,对等式约束条件开发了罚函数法和解方程法的求解步骤,并进行了分析比较,从而形成了完整的求取非线性规划问题全局优化的模拟退火算法。

Under suitable assumptions, the relationship is established between the unconstrained minimization of the Hestenes-Powell augmented Lagrangian function on the space of problem variables and the solution of the original constrained problem, and a relationship is also presented between the unconstrained minimization of the Hestenes-Powell augmented Lagrangian function on the product space of problem variables and multipliers and the solution of the original constrained problem.

在适当的条件下,我们建立了Hestenes-Powell增广拉格朗日函数在原问题变量空间上的无约束极小与原约束问题的解之间的关系,并且也给出了Hestenes-Powell增广拉格朗日函数在原问题变量和乘子变量的积空间上的无约束极小与原约束问题的解之间的一个关系。

The shock pressure of booster HMX/F2641 with smaller charge diameter was determined under three sorts of restraint conditions through manganin manometric method, and the test results were discussed according to shock kinetics.

采用锰铜测压实验测定了较小装药直径下,强约束、弱约束及无约束条件下传爆药HMX/F2641的输出压力,并运用冲击动力学进行了探讨,混合炸药实验密度为90%的理论密度。

The reconstruction problem is ill-posed, so two optimal criterions, the least module and the smoothness criterion base on Tikhonov regularization technique, are introduced into reconstruction algorithm. Many regularization parameters choice strategies are investigated, and the TPA(Two—Parameter Algorithm) strategy which is based on the Morozov discrepancy principles, is implemented in two regularization reconstruction algorithms.Numerical experiment results show that the nonnegative and smoothness constraint condition can overcome the difficulty of iteration semiconvergent, preconditioned technique can improve convergence rate and reconstruction accuracy, smoothness regularization criterion can meliorate ill-posed problem of reconstruction and enhance iteration stability, and the TPA is an effective strategy of regularization parameters choice.

数值试验表明:在共轭梯度法中引入非负约束和光滑约束改善了迭代的"半收敛"性,非负约束保证了解的非负性,光滑约束抑制了重建解的振荡现象,约束算法的重建精度与无约束算法相比大幅度提高;在约束共轭梯度重建算法中引入预优技术,可以加快算法的收敛速度,提高迭代的稳定性和重建精度;引入光滑准则的正则化技术可以有效改善图像重建问题的不适定性,加快迭代的收敛速度,提高迭代的稳定性和图像重建质量,计算正则参数的TPA算法在闪光照相图像重建中是有效的。

With the primary goal function, the optimization problem is changed to a nonrestraint one.

在无约束优化过程中,通过逐步增大罚因子,使无约束优化问题的解逼近原约束优化问题的解,用随机搜索优化方法得到了拱坝的优化体型。

The reconstruction problem is ill-posed, so two optimal criterions, the least module and the smoothness criterion base on Tikhonov regularization technique, are introduced into reconstruction algorithm. Many regularization parameters choice strategies are investigated, and the TPA(Two—Parameter Algorithm) strategy which is based on the Morozov discrepancy principles, is implemented in two regularization reconstruction algorithms.Numerical experiment results show that the nonnegative and smoothness constraint condition can overcome the difficulty of iteration semiconvergent, preconditioned technique can improve convergence rate and reconstruction accuracy, smoothness regularization criterion can meliorate ill-posed problem of reconstruction and enhance iteration stability, and the TPA is an effective strategy of regularization parameters choice.

数值试验表明:在共轭梯度法中引入非负约束和光滑约束改善了迭代的&半收敛&性,非负约束保证了解的非负性,光滑约束抑制了重建解的振荡现象,约束算法的重建精度与无约束算法相比大幅度提高;在约束共轭梯度重建算法中引入预优技术,可以加快算法的收敛速度,提高迭代的稳定性和重建精度;引入光滑准则的正则化技术可以有效改善图像重建问题的不适定性,加快迭代的收敛速度,提高迭代的稳定性和图像重建质量,计算正则参数的TPA算法在闪光照相图像重建中是有效的。

In this paper, the Hestenes-Powell augmented Lagrangian function is again considered, for solving equality constrained problems via unconstrained minimization techniques.

在适当的条件下,我们建立了Hestenes-Powell 增广拉格朗日函数在原问题变量空间上的无约束极小与原约束问题的解之间的关系,并且也给出了Hestenes-Powell 增广拉格朗日函数在原问题变量和乘子变量的积空间上的无约束极小与原约束问题的解之间的一个关系。

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