提出了一种基于牛顿法的三相配网状态估计算法。
A three phase distribution system state estimation algorithm is proposed in this paper which based on Newton method.
本文提出了一种新的快速解耦配电网状态估计算法。
A new fast decoupled state estimation method is presented for distribution systems.
研究了单测站测量的火箭飞行测量数据的状态估计算法。
A state estimation algorithm of the rocket flight path under single station measurement is studied.
状态估计算法的研究直接关系到状态估计计算的速度、精度等。
The algorithm of SE is related to the speed and precision of calculating directly.
提出了一种基于相坐标系的配电网三相不对称解耦的状态估计算法。
A new algorithm for state estimation based on the fast decoupling of distribution system's asymmetrical phases in phase coordinates is proposed.
提出考虑配电馈线环网和节点零注入的基于支路电流的状态估计算法。
Considering meshed network of distribution feed lines and node zero injection, we put forward a algorithm of status estimation based on branch currents.
在符号动力学的基础上，提出了全局耦合映像格子系统的初始状态估计算法。
An initial condition estimation algorithm for global coupled map lattice systems based on the symbolic sequence is proposed.
因此，本文对基于等效电流量测变换的电力系统状态估计算法进行了研究分析。
Therefore, state estimation algorithm based on the measurement transformation of the equivalent current is studied in this paper.
文摘：提出了一种新的三相状态估计算法，并详细地阐述了一种三相状态估计的处理策略。
Abstract: a new three-phase state estimation algorithm is proposed and its details are presented in this paper.
在线性无偏最小方差估计准则下，推导出了该离散化后所得系统的全局最优递推状态估计算法。
In the sense of linear unbiased minimum variance estimation, a global optimal recursive state estimation algorithm for this discretized linear system is proposed.
有一些类型的工作项包含了与时间计算相关的信息，而有的则不含，所以我们必须使用不同的算法，来估计不同类型工作项的工作项状态。
Some types of work items contain information relative to the time scales, and others do not, so we have to use different algorithms to calculate the work item status of different types of work items.
在卫星的状态估计过程中应用推广的序列估计算法，借助数值积分方法积分状态向量和协方差矩阵。
For the estimation of satellite state, the extended sequential estimation algorithm was applied. The numerical method was used to integrate state vector and error covariance matrix.
将未知噪声统计量的估计与信号状态估计交替进行的算法引入G P S定位，计算机模拟结果表明效果很好。
Estimation of unknown noise statistics quantity and estimation of signal states are alternatively done, this method is applied to GPS positioning, Computer simulation shows the approach is efficient.
本文主要针对多通道带乘性噪声系统的观测噪声最优估计算法和状态最优融合估计算法展开进一步研究。
The optimal estimation algorithm of measurement noise and the optimal state fusion algorithm for multi-channel system with multiplicative noises are mainly researched in this dissertation.
两个不同的蒙特卡罗仿真表明，通过采用这一新算法引人径向速度测量，不仅可以大大提高状态估计的精度，而且其估计性能和计算效率优于传统的EKF。
Two different Monte Carlo simulations show that the new algorithm cannot only improve state estimation accuracy but also is superior to EKF in estimation performance and computation efficiency.
这种建立模型的思想还可以应用到需要计算海森矩阵的动态无功优化、最优潮流以及状态估计等问题的算法中，以提高其计算速度。
This proposed modeling idea can also be applied to dynamic reactive optimization, optimal power flow and state estimation for a faster calculation.
该算法具有常数的雅克比矩阵，大大减少了动态状态估计的计算时间，同时保证了动态状态估计的计算精度。
Since the proposed algorithm has a constant Jacobian matrix, the calculating time can be significantly reduced, while the calculating precision can also be guaranteed.
基于多传感器多模型信息，给出了目标状态基于全局信息融合估计的一种新算法，并通过计算机仿真验证了这种算法的有效性。
Based on Multi_sensor Multi_model information, we present a new algorithm based on total information fusion estimation on target state. We prove the validity of this algorithm by computer.
在算法的状态估计阶段，采用混合系统粒子滤波和二元估计算法同时估计对象系统故障演化模型混合状态和未知参数的后验分布。
For state estimation of hybrid system with unknown transition probabilities, an adaptive estimation algorithm is proposed based on Monte Carlo particle filtering.
在算法的状态估计阶段，采用混合系统粒子滤波和二元估计算法同时估计对象系统故障演化模型混合状态和未知参数的后验分布。
For state estimation of hybrid system with unknown transition probabilities, an adaptive estimation algorithm is proposed based on Monte Carlo particle filtering.
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