片语

convex secondary optimization凸二次优化

convex programming凸规划

Convex Optimization Theory凸优化理论

linear convex optimization线性凸优化方法

nonlinear convex constrained optimization凸约束的非线性规划问题

convex vector optimization凸向量优化

convex constrained optimization凸约束优化

convex quadratic optimization凸二次规划

Convex x Optimization凸优化

non-convex optimization非凸优化

convex composite optimization复合凸优化

英汉例句

• The robust stable bound and the state feedback controller can be obtained by solving a class of convex optimization problems with LMI constraint.

  系统的稳定界和反馈控制器可以通过求解一类线性矩阵不定式约束的凸优化问题得到。

• The convex optimization algorithm was used to get the minima upper bound of performance cost and parameter of optimal minimax controller.

  引入凸优化算法，求解使闭环系统渐近稳定且性能指标上界最小的最优控制器参数。

• In this thesis, we study two related problems: convex optimization problems and equilibrium problems.

  凸优化问题与平衡问题密切相关，本文对这二类问题进行研究。

• Furthermore, a convex optimization problem with LMI constraints is formulated to design the optimal guaranteed cost controllers.

  通过求解一个线性矩阵不等式约束的凸优化问题，提出了最优化保性能控制律的设计方法。

• The paper constructs a new optimal target function for feed forward neural networks according to convex optimization theory and constraint optimization theory.

  该文利用凸优化理论和约束优化理论为前馈神经网络构造出了一个新的优化目标函数。

• On the basis of convex optimization theory, the design arithmetic method and its steps about optimal guaranteed cost reliable control are provided.

  根据凸优化理论，最优保性能标準控制器和最优保性能可靠控制器的设计方法转化为一个线性凸优化算法。

• Converting the convex optimization question to simple one dimension search, we get the effective method to settle the optimal weight coefficient.

  通过转换该凸最优的约束方程为简单的一维搜索，提出了最优加权系数的有效求解方法。

• On the basis of convex optimization theory, the design method about optimal guaranteed cost reliable controller and standard controller transform convex optimization arithmetic.

  根据凸优化理论，最优保性能标準控制器和最优保性能可靠控制器的设计方法转化为一个线性凸优化算法。

• Many important problems of system and control theory can be reformulated as linear matrix inequality convex optimization problems, which is numerically tractable.

  系统与控制理论中的许多问题，都可转化为线性矩阵不等式约束的凸优化问题，从而简化其求解过程。

• Using the linear matrix inequality (LMI) technique, the problem is converted into a linear convex optimization algorithm so that a global optimization solution is obtained. Finally.

  采用线性矩阵不等式技术，将问题转化为一线性凸优化算法，可得问题的全局最优解。

• Second, tensor completion is formulated as a convex optimization problem. A closed form for augmented Lagrangian function is obtained via relaxation technique and separation of variables technique.

  其次，把张量补全作为一个凸优化问题建模，利用松弛技术和变量分离技术得到闭合的增强拉格朗日函数；

• This paper presents an interior trust region method for linear constrained LC convex optimization problems.

  本文提出一种解线性约束凸规划的数值方法。

• This paper discusses problems arising in system and control theory to a few standard convex optimization problems involving linear matrix inequality (LMI).

  本文研究了出现在系统与控制理论中的一些标準的、包含线性矩阵不等式的凸优化问题。