介绍了基于动态系统可观测性矩阵奇异值分解的状态变量可观测度的分析方法。
The method of analyzing the observable degree of the state variable has been introduced by means of the singular value decomposition (SVD) of the observable matrix of a dynamic system.
对于线性系统，其可观测性可通过对可观测性矩阵的分析获得，但并不能求出系统的观测度。
The observability of linear timeinvariant dynamic system can be obtained by the analysis of the observable matrix, but it can not give the observability.
为了便于利用现有的正常系统研究结果，运用矩阵的约当分解，将一类广义系统化为正常系统，并保持其可观测性不变。
For the sake of using the research of normal systems easily, descriptor systems are changed into normal systems by using Jordan decomposition of matrixes and their observability is hold on.
还提出了一种基于节点邻接矩阵的快速可观测性分析方法。
In addition a speedy observability analysis method based on nodal adjacent matrix is put forward.
提出了一种新的基于降阶网络雅可比矩阵的电力系统状态估计可观测性分析方法。
A new observability analysis algorithm for power system state estimation based on reduced network Jacobian matrix is proposed.
然后，通过对误差方差阵逆矩阵秩的分析，比较详尽地分析了不同数量视线观测条件下导航算法的可观度和可观性。
Then, navigation system observability and observable degree with different quantitative line-of-sight measurements are analyzed in detail by rank analysis of the error variance inverse matrix.
然后，通过对误差方差阵逆矩阵秩的分析，比较详尽地分析了不同数量视线观测条件下导航算法的可观度和可观性。
Then, navigation system observability and observable degree with different quantitative line-of-sight measurements are analyzed in detail by rank analysis of the error variance inverse matrix.
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