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.
本文主要研究了具有不确定参数的线性二次型高斯问题(LQG)的对偶自适应控制问题。
This thesis discusses the dual adaptive control in Linear Quadratic Gaussian (LQG) with uncertainty parameters 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.
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