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• 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优化问题，提出了最优化保性能控制律的设计方法。

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• In convex programming theory, a constrained optimization problem, by KT conditions, is usually converted into a mixed nonlinear complementarity problem.

规划理论中，通过KT条件往往约束最优化问题归结一个混合互补问题来求解。

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• The problem is reduced to a linear convex optimization algorithm via LMI approach.

采用线性矩阵不等式方法，将问题转化为一个线性优化算法

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• SVM transforms machine learning to solve an optimization problem, and to solve a convex quadratic programming problem by the optimization theory and method constructing algorithms.

它将机器学习问题转化为求解最优化问题应用最优化理论构造算法解决二次规划问题。

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• The optimization problem can be solved based on the density-stiffness interpolation scheme and the method of moving asymptotes belonging to sequential convex programming approaches.

采用基于密度刚度插值模型序列规划法中的移动渐近线方法求解优化模型。 通过经典算例验证了本方法的有效性。

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• Reliability index Robust Convex model Optimization problem;

可靠性指标稳健模型优化问题

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• 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问题转化线性优化算法，可问题全局

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• The problem of resource allocation in this scheme is a non-convex non-linear optimization problem.

模型中的资源分配问题一个非凸非线性优化问题

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• On the conditions that vector objective function is like-convex and quasi-convex, we obtain the connectedness of G-proper efficient solution set of the multiobjective optimization problem.

此基础上，得到向量目标函数既是似凸又是拟凸目标最优化问题的G-恰当有效是连通的结论。

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• On the conditions that vector objective function is like-convex and quasi-convex, we obtain the connectedness of G-proper efficient solution set of the multiobjective optimization problem.

此基础上，得到向量目标函数既是似凸又是拟凸目标最优化问题的G-恰当有效是连通的结论。

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