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.
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。
This thesis discusses the dual adaptive control in Linear Quadratic Gaussian (LQG) with uncertainty parameters 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。
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