本文提出了一种求解二进制二次规划问题的连续化方法。
A continuous approach to solving general binary quadratic problems is investigated.
针对凸约束非凸二次规划问题，给出了一个分枝定界方法。
In this paper, a branch-and-bound method is proposed for non-convex quadratic programming problems with convex constrains.
因此标准的SVM方法需要求解二次规划问题，计算量很大。
The standard SVM requires solving quadratic program that needs considerably longer computational time.
本文改进了带线性约束0 - 1二次规划问题的罚参数下界。
In this paper, penalty parameter for linearly constrained 0-1 quadratic programming is improved.
现有的大多数分类问题都能转化成一个正定二次规划问题的求解。
Most existed classification problems can be converted into a positive definite quadratic program.
滚动时域估计的基本策略就是将状态估计问题化为一个二次规划问题。
The basic strategy of MHE is to reformulate the estimation problem asa quadratic program using a moving estimation window.
对于大规模的具有伪凸目标函数的二次规划问题，本文提出一种分解算法。
This paper proposes a decomposition algorithm for large scale quadratic programming with a pseudoconvex objective function.
在本文中，我们提出了一种解带有二次约束二次规划问题(QP)的新算法。
In this paper we present a new algorithm for solving quadratic programming problem (QP) with quadratic constraints.
这些新的结论都表明了该神经网络在求解有界约束二次规划问题时的有效性。
All these new results show the validity of the network in solving quadratic optimization with bound constraints.
提出一种求解二次规划问题的方法。这种方法可快速、准确地得到问题的解。
Presents a method to solve quadratic programming problems with advantages of quickness and accuracy.
本文利用统计学中线性模型的理论给出一类等式约束二次规划问题解的表达式。
In this paper, using the theories of linear model in the statistics, we can give the general expression on solution of a class of equality constrained quadratic programs problem.
在第三章，我们提出了一种解决具有边界约束的正定二次规划问题的对偶方法。
In chapter 3, we presented a dual method for solving positive definite quadratic programming with box constraints.
考虑了广义二次规划问题，基于其鞍点的充要条件，提出了求解它的一个神经网络。
This paper considers the extended quadratic programming problem. Based on the necessary and sufficient conditions for a saddle point, a neural network for solving it is proposed.
该模型通过引入权系数，使多目标问题转化为一个二次目标、线性约束的二次规划问题。
The weight coefficient was introduced into the model, and the multi-objective problem was changed into a quadratic-programming problem.
在第二章，我们提出了一种解决具有原方块角形结构正定二次规划问题的分解协调算法。
In chapter 2, we presented a method for solving positive definite quadratic programming with coupled-block structure.
提出了一种解带有二次约束二次规划问题的新的分枝定界算法对该算法进行了收敛性分析。
We present a new branchandbound algorithm for solving quadratic programming problem with quadratic constraints, and analyze the convergence of the algorithm.
建立了道路识别问题的数学模型并将上述问题与一个不等式约束的正定二次规划问题相联系。
A mathematic model of road identification problem is provided and the problem is related with a positive definite quadratic programming problem with inequality constraints.
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.
另外，支持向量机的求解最后转化成二次规划问题的求解，因此支持向量机的解是唯一的也是全局最优解。
In addition, the solutions of SVM transform to the solutions of quadratic programming problems at last. SVM is thus the only solution and the global optimal solution too.
训练支持向量机的本质问题就是求解二次规划问题，但对大规模的训练样本来说，求解二次规划问题困难很大。
The key problem of training support vector machines is how to solve quadratic programming problem, but for large training examples, the problem is too difficult.
大量的关于随机的凸二次规划问题的数值实验结果表明它的计算效率是高的，在某些条件下可能是多项式时间算法。
Some numerical results for a large number of random convex quadratic programming problems show that the new algorithm is efficient and might be a polynomial-time algorithm under some conditions.
该算法能针对在样本有限的情况下，采用结构风险最小化准则，把学习问题转化为一个二次规划问题来获得最优解。
The method can transfer the learning problem into a second planning to acquire the optimal solution according to the principle of structure risk minimum under limited samples situation.
把高维线性互补问题转化为与之等价的高维二次规划问题，然后把高维二次规划问题分解为一系列低维二次规划问题。
The higher dimensional linear complementary problem is transformed into quadratic (programming), and then decomposed into a series of lower dimensional quadratic programming.
所运用的线性不等式组的一种旋转算法避免了通常处理二次规划问题所需的松弛变量、剩余变量和人工变量，操作简便、计算效率高。
The algorithm solves the quadric programming problem without adding slack, remaining and artificial variables while its efficiency is very high and it operates very easily.
采用椭球剖分策略剖分可行域为小的椭球，用投影次梯度算法解松弛二次规划问题的拉格朗日对偶问题，从而获得原问题的一个下界。
A projection subgradient algorithm for the Lagrangian dual problem of the relaxed quadratic problem is employed to general lower bounds of the optimal value for the original problem.
根据混合逻辑动态系统的标准形式，转化为混合整数二次规划(MIQP)的问题，同时获得它的数学描述。
According to the standard form of MID system, the problem of mixed integer quadratic programming (MIQP) and its mathematics description can be obtained.
针对处理任务分配，将其建模为二次0 - 1规划问题，并提出了分布式逐层优化分配算法oall。
The processing task assignment is formulated as a quadratic 0-1 programming problem, and a distributed OALL algorithm (optimizing assignment layer by layer) is proposed.
针对处理任务分配，将其建模为二次0 - 1规划问题，并提出了分布式逐层优化分配算法oall。
The processing task assignment is formulated as a quadratic 0-1 programming problem, and a distributed OALL algorithm (optimizing assignment layer by layer) is proposed.
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