投影定理 meaning in Chinese
projection theorem
Examples
- 3 . use the boasting dates of every bo , we atup the dea rnodel , such as c ' r and c : gs : . w wt is m as a theis , and it ' s relative efficiency is evalwt by the m , we ahalysis bo taal effiwt and scale effeency a clear ditw is given bo the dea effiho dmus nd the no dea effich we also can for m insghthe - - boon with the bokgroun
构造具有非阿基米德无穷小量的dea模型c2r和c2gs2 ，对调整前后农业产业系统的综合生产能力和生产效率进行评价，体现了不同调整方案的结构优化效应，并对各方案进行规模效益和投入冗余率、产出不足率分析：运用投影定理构造“虚拟”决策单元，对方案进行修正和改进。 - A filtering algorithm for system with multiplicative noise is developed under the condition that the multiplicative noise is in the form of a general stochastic matrix and each component of the multiplicative noise matrix is correlated at the same time . the algorithm is optimal in the sense of linear minimum - variance
基于投影定理，在各个通道的乘性噪声同时刻相关，且加性噪声同时刻相关和不相关的情况下，推导出了状态滤波递推算法，该算法在线性最小方差意义下是最优的。 - The deducing of the algorithms has very practical value in state estimation for systems under the complex environments . in the instance of complicated multi - channel system with multiplicative noise , the dissertation discusses the optimal estimation of state filtering and smoothing and the stochastic input signal with the technique of innovation and projection theorem of hilbert space . the main study of the dissertation is introduced as follows : 1 according to the practical requirement of complicated multi - channel system with multiplicative noise , the dissertation broadens rajasekaran filtering algorithm
本文针对复杂多通道带乘性噪声系统，应用新息的方法和hilbert空间的投影定理，对状态最优滤波和平滑估计、随机输入信号的最优估计等理论与应用方面的问题，进行了进一步的探讨，着重完成了以下工作：第一，根据复杂多通道乘性噪声系统问题的实际需要，推广了rajasekaran滤波算法。 - Based on the foundational properties of centrosymmetric matrix and anti - centrosymmetric matrix , employing the technology of lowing dimension , the generalized inverse eigenvalue problems which involve centrosymmetric matrix , anti - centrosymmetric matrix , and compound centrosymmetric matrix and anti - centrosymmetric matrix , have been discussed . on the basis of above , and employing projection theory , the optimal approximation of them under spectral constraints has been solved
在中心对称矩阵和反中心对称矩阵的基本性质基础之上，利用分块降维技术来简化问题，本文讨论了中心对称矩阵，反中心对称矩阵，混合中心对称矩阵与反中心对称矩阵，三类广义逆特征值问题，并在此基础上利用投影定理解决了它们在谱约束下的最佳逼近问题。