Objective: To search optimal solutions of convex programming problems with linear constraints.
求线性约束凸规划问题的最优解。
This paper first presents a branch-and-bound algorithm to minimize a finite sum of stair-case functions under linear constraints.
该文首先给出了求在线性约束下极小化有限个阶梯函数和的一种分枝定界算法。
In this paper, we present an exact algorithm for solving nonseparable convex knapsack problems with linear constraints and bounded integer variables.
本文对线性约束不可分离凸背包问题给出了一种精确算法。
The paper studies the nonlinear programming problem with linear constraints. Based on its optimality conditions, a neural network for solving it is proposed.
研究了线性约束的非线性凸规划问题，基于最优性的充要条件，提出了求解它的一个神经网络。
In this paper, a new generalized gradient projection method with inexact line search is proposed for the nonlinear optimization problem with linear constraints.
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。
Based on internal algorithm, a generalized variable metric projection internal algorithm for nonlinear programming with linear constraints and the convergence proof are given.
基于内点算法的思想，利用广义投影技术构造了一求解线性约束的非线性规划问题的变尺度方向内点算法，并给出了其收敛性证明。
This kind of beamformer can eliminate incoherent noise when signals pass Wiener filter, then achieve a better speech-enhance effect by linear constraints minimum variance beamforming.
该波束形成器首先让信号经过维纳滤波器消除非相干噪声，而后经过经典的线性约束最小方差处理，最终达到较好的语音增强效果。
This kind of beamformer can eliminate incoherent noise when signals pass Wiener filter, then achieve a better speech-enhance effect by linear constraints minimum variance beamforming.
该波束形成器首先让信号经过维纳滤波器消除非相干噪声，而后经过经典的线性约束最小方差处理，最终达到较好的语音增强效果。
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