convex quadratic programming

基本解釋

Lower approximation algorithm and its solve of convex quadratic programming are also given in this article.
混合優(yōu)化控制算法，給出了求解最優(yōu)控制器的上逼近算法及其凸二次規(guī)劃求解方法。
In this paper, a branch-and-bound method is proposed for non-convex quadratic programming problems with convex constrains.
針對(duì)凸約束非凸二次規(guī)劃問(wèn)題，給出了一個(gè)分枝定界方法。
A new gradient-based neural network for solving convex quadratic programming problems is proposed by means of the inherent properties of the original problem.
根據(jù)問(wèn)題自身的結(jié)構(gòu)特點(diǎn)，通過(guò)將其轉(zhuǎn)化為等價(jià)的方程，提出了求解凸二次規(guī)劃的一個(gè)基于梯度的新神經(jīng)網(wǎng)絡(luò)模型。