awhere f (x) , g; (x) and r are the objective func-tion, the ph inequality constraint function, and the penalty parameter. This functional is exact in the sense that local minimums of the functional are equivalent to local minimums of the original problem to a large extent. The augmen...
作者: R Nishii 摘要: In this paper, we give a survey of optimality of experimental designs. The equivalence theory between optimalities is discussed using the directional derivative of the criterion function. Optimality based on the mean squared error is also treated and, in particular, is ...
Belavkin, R.V.: Bounds of optimal learning. In: 2009 IEEE International Sympo- sium on Adaptive Dynamic Programming and Reinforcement Learning, Nashville,... RV Belavkin - IEEE Symposium on Adaptive Dynamic Programming & Reinforcement Learning 被引量: 11发表: 2009年 Asymptotically Efficient Adapti...
发协 议 (joint R & D pacts) 和联合 发展 协议 (joint develop men t ag reement s ) 。 本文 的贡献 在 于利用新 制度 经济 学 中的外部 性理 论分 析 了京津冀 产业 的外部 性 以及 转 化为 内 部性 的途径 ;利用帕 累托 最优 理论 分析 了京 津冀 联盟 的效率 。结合 京津...
作者: R Olfati-Saber 摘要: One of the fundamental problems in sensor networks is to estimate and track the state of targets(or dynamic processes) of interest that evolve in the sensing field. Kalman filtering has been an effective algorithm for tracking dynamic processes for over four decades....