In this paper, we present a convergent result of the iterative solution methods for a class of generalized saddle point problem, which lowers the condition of the recent results.
给出一类广义鞍点问题迭代解法的收敛性分析结果，降低了目前已有相关结论的适用条件，因而使得相关结果具有更广泛的应用性。
This paper studies the numerical problem of the saddle point strategy for linear quadratic differential game in generalized state systems.
研究广义状态系统中线性二次型微分对策鞍点策略的数值求解问题。
Problem Set2: Continuum approximations of non-stationary random walks, random walk in a harmonic well, steps with fat tails, saddle-point asymptotics.
问题2：非稳定型随机漫步的连续极限，具调合井的随机漫步，具备巨大尾部的漫步，鞍点近似解。
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.
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。
Under the nearly cone-subconvexlike set-valued maps, relations of strong efficient solutions and Kuhn-Tucker saddle point of set-valued optimization problem are dicussed.
集值优化问题的最优性条件与解集的结构理论在集值优化理论中占有重要的地位。
Under the nearly cone-subconvexlike set-valued maps, relations of strong efficient solutions and Kuhn-Tucker saddle point of set-valued optimization problem are dicussed.
集值优化问题的最优性条件与解集的结构理论在集值优化理论中占有重要的地位。
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