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。
The paper constructs a new optimal target function for feed forward neural networks according to convex optimization theory and constraint optimization theory.
该算法基于凸优化理论，对功率分配、子载波配对、中继选择和用户选择进行了联合优化。
Based on the convex optimization, the algorithm jointly optimizes power allocation, subcarrier pairing, relay selection and user selection.
根据凸优化理论，最优保性能标准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。
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，最优保性能标准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。
On the basis of convex optimization theory, the design arithmetic method and its steps about optimal guaranteed cost reliable control are provided.
本文研究了出现在系统与控制理论中的一些标准的、包含线性矩阵不等式的凸优化问题。
This paper discusses problems arising in system and control theory to a few standard convex optimization problems involving linear matrix inequality (LMI).
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。
Many important problems of system and control theory can be reformulated as linear matrix inequality convex optimization problems, which is numerically tractable.
在凸规划理论中，通过KT条件，往往将约束最优化问题归结为一个混合互补问题来求解。
In convex programming theory, a constrained optimization problem, by KT conditions, is usually converted into a mixed nonlinear complementarity problem.
它将机器学习问题转化为求解最优化问题，并应用最优化理论构造算法来解决凸二次规划问题。
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.
函数的凸性与广义凸性在数学规划以及最优化理论中起着非常重要的作用。
Convexity and generalized convexity of functions play an important role in mathematical programming and optimal theory.
本文将4／6极和8／12极两种不同结构双凸极永磁电机进行详细比较，从而为该电机的优化设计进一步深入研究提供理论依据。
This paper will compare 8/12 DSPM with 4/6 DSPM in detail, and provide theoretic basis for design and research deeply of DSPM.
应用已有的极点理论，优化相伴凸组合的界并改进整数规划问题的目标函数及变量的界。
Assuming knowledge of extreme points, we develop bounds for associated convex combinations and improve bounds on the integer programming problems objective function and variables.
本文研究了出现在系统与控制理论中的一些标准的、包含线性矩阵不等式的凸优化问题。
In this paper, a new generalized gradient projection method with inexact line search is proposed for the nonlinear optimization problem with linear constraints.
而最优化理论的许多有意义的重要结果大都建立在凸性和某些广义凸性的假定上。
And many meaningful and important results in the optimization theory was base on the the convex and some assumptions on the convexity.
而最优化理论的许多有意义的重要结果大都建立在凸性和某些广义凸性的假定上。
And many meaningful and important results in the optimization theory was base on the the convex and some assumptions on the convexity.
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