convex optimization

in these models, the localization problem is modeled as a convex optimization problem which takes the minimum distance error as the objective function, and the distance between nodes as the constraints, and then relaxed to an easy problem by related relaxation techniques.

模型中以最小化节点间距离误差为目标函数，节点间距离为约束，将节点定位问题建模成一个凸优化问题，并利用相关松弛技术将模型松弛为容易求解的问题。

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Semidefinite programming is a branch of convex optimization problem. Important applications of semidefinite programming exist in combinatorial optimization, approximation theory, system and control theory, and mechanical and electrical engineering.

半定规划是凸规划的一个重要分支，并且半定规划在组合优化、逼近理论、系统控制理论、机械及电子工程中有着广泛的应用。

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hence, the thesis does an in-depth study on the physical-layer security based on an with convex optimization as math tools. it focuses on the secret communications in multi-input single-output ( miso) systems and cognitive radio networks and their robustness design.

因此，以凸优化理论为数学工具，本文对基于人工噪声的物理层信息安全进行深入研究，重点研究多输入单输出（MISO）系统和认知无线电网络的保密通信的鲁棒性设计。

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For some special cases, the deterministic convex optimization problems are derived.

对某些特殊的情形, 我们导出了鲁棒线性最优化的确定性等价问题.

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Robust control law with a smaller gain is received via solving a class convex optimization with LMI constrains.

该控制律的求解，借助求解一类具有线性矩阵不等式（LMI）约束的凸优化问题。

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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。

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This paper presents an interior trust region method for linear constrained LC ^ 1 convex optimization problems.

摘要本文提出一种解线性约束凸规划的数值方法.

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Make a more comprehensive comparison and improvement about distributed convex optimization methods deal with model training.

对核心模型训练涉及的分布式的凸优化方法做了比较全面的对比和改进。

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A new method using convex optimization and projection is proposed to design the low-order cont roller.

提出一种将凸优化算法和投影原理相结合的降阶控制器设计新方法.

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Global convergence for the algorithm is established under the assumption that the objective function is bounded from below, The authors also generalize the algorithm to constrained convex optimization and obtain the convergence that is the same as unconstrained algorithm.

此外还把算法推广到约束凸规划问题，得到了与无约束问题同样的收敛结果，如果约束是线性的，则算法是数值可行的。

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the interior-point method for convex optimization is presented here as a computationally efficient tool.

推导给出该凸优化模型对应的拉格朗日函数及KKT条件，并引入凸优化内点法作为负荷分配的有效计算工具。

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By norm consistency principle and triangle inequality, the problems of minimizing the Frobenius norm of jump vector and the upper bound of quadratic cost function are turned into a convex optimization problem containing linear matrix inequalities constraints.

利用范数相容性原理和三角不等式，将最小化跳变向量Frobenius范数和二次型成本函数上界问题转化为一个具有线性矩阵不等式约束的凸优化问题。

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