1) extending Kalman filtering method
扩张Kalman滤波法
1.
Based on different defect velocities in the simulated model, the stability of the extending Kalman filtering method is illustrated by the simulation calculation.
利用扩张Kalman滤波法求解超声波CT反演计算中的大型稀疏方程组。
2) Kalman filter
Kalman滤波法
1.
This paper presents a new way to estimate the measurement variance of noise in the analytical chemistry signals for the Kalman filter by means of implementing the wavelet analysis, according to that wavelet transformation can separate the noise in high frequency band from the original signal.
根据小波变换能从原始信号中分离高频段噪声的特性 ,本文提出一个用小波分析法从分析化学信号中估计Kalman滤波法所需要的噪声测量方差的新途径。
2.
Compared with traditional ones such as Kalman filter and least squares, the technique results in more accurate estimations of OD split proportions.
与诸如Kalman滤波法和最小二乘法等方法相比,该技术会使得OD分配比例的预测更加精确。
3.
Based upon the principles of Kalman filter method,the authors defined a new parameter,relative chemomic error(ε),to evaluate the asynchronous nature of the components in TCMs,and a derivative parameter as synchronization factor(SF) to quantify the synchronicity of the chemome .
基于Kalman滤波法原理,定义了化合物组异步性特征参数"化合物组相对误差(relative chemomic error,ε)",并据此建立同步性参数"同步性因子(synchronization factor,SF)"和反映化合物组释放同步性的参数"平均同步因子(average synchronization factor,SFav)"等评价参数。
3) Kalman filter method
Kalman滤波法
1.
The released chemomic levels of TCMs were processed by Kalman filter method with stochastic simulation data as an illustration of the methodology feasibility.
方法:基于中药化合物组的整体谱特征,运用Kalman滤波法,计算获得溶出介质中化合物组含量,建立多组分中药的化合物组释放/溶出动力学评价理论;采用随机模拟数据,验证Kalman滤波法评价化合物组释放度的可行性,举例说明多组分中药化合物组释放/溶出动力学的计算方法。
2.
And combined with project example,it introduces the application of Kalman filter method in linear control,points out that the key problem of linear control is deciding the construction camber of beams.
通过对预应力混凝土连续箱梁桥悬臂浇筑施工的研究,阐述了线形控制的基本原理,并结合工程实践介绍了Kalman滤波法在线形控制中的应用,指出线形控制的关键问题在于合理确定梁段施工预拱度。
4) Extended Kalman filter
扩展Kalman滤波
1.
The minimum meansquare values currently used in fault diagnosis can only get the static estimate values,and although the extended Kalman filter(EKF) can realize dynamic parameter estimation,yet for a nonlinear system,a single EKF does not exhibit good ability for either the normal process or the fault process.
如果采用最小二乘算法,参数估计是静态的,故障诊断延迟一般较大;采用单模型扩展Kalman滤波算法,虽然能够实现动态估计,但不能同时兼顾稳态过程和过渡过程(突发故障)的参数估计,导致误差较大。
2.
A novel learning algorithm for wavelet neural network based on Extended Kalman Filter is proposed to predict the deformation of structure.
提出一种新颖的用于变形预测的基于扩展Kalman滤波的小波神经网络学习算法,与BP算法相比,该方法具有更好的收敛率和学习能力,并通过实例计算证明了该方法具有较高的精度和较快的计算速度。
3.
A new learning algorithm for a multilayered neural network based on extended Kalman filter is proposed to predict the deformation of structure.
给出了一种用于变形预测的基于扩展Kalman滤波的神经网络学习算法,与BP算法相比,该方法具有更好的收敛率和学习能力。
5) extended Kalman filter(EKF)
扩展Kalman滤波
1.
It is shown,by comparison and analysis that the UKF algorithm is better than extended Kalman filter(EKF) and the adaptive EKF is superior to UKF,and the adaptive UKF is superior to all algorit.
计算结果表明,在GPS/INS松组合导航系统数据处理时,UKF算法略优于扩展Kalman滤波(EKF),自适应UKF算法优于自适应EKF算法,自适应UKF算法能够很好地抑制动力学模型误差对导航解的影响,进一步提高导航解的精度和可靠性。
2.
At present the relatively widely used terrain aided navigation(TAN) method is based on extended Kalman filter(EKF).
传统地形辅助导航中应用较为广泛的是扩展Kalman滤波方法,但因为地形高度测量的非线性,扩展Kalman滤波不一定能够得到系统最优估计。
3.
Secondly,a spherical-coordinate based extended Kalman filter(EKF)is adopted to estimate the delay range and the smaller ones can be viewed as being from physical targets while the larger ones can be viewed as active decoys.
首先,将假目标的延迟距离增广到球坐标系的状态矢量中,从理论上导出了弹道目标更一般意义下的运动方程;其次,利用球坐标下的扩展Kalman滤波(EKF)对延迟距离进行实时估计,延迟距离较小的判定为实体目标,延迟距离较大的判定为有源假目标;最后,分析了相关因素对跟踪和鉴别性能的影响。
6) extend Kalman filter
扩展Kalman滤波
1.
In order to choose reasonable strategies to deal with nonlinear models in filter, the extend Kalman filter, Bancroft algorithm and refined measure equationsby using surveying information are analyzed and com-.
为此,分别讨论了扩展Kalman滤波和Bancroft算法以及利用观测信息迭代精化观测方程三种算法,并结合算例进行了比较与分析。
2.
The autonomous navigation is implemented by Extend Kalman Filter (EKF) using the selenocentric direction and the selenocentric distance, which are measured by the ultraviolet moon sensor and the altimeter respectively.
本文以f-g 级数形式推导出了小时问间隔情况下的月球探测器状态传播方程,研究了以紫外月球敏感器测量的月心方向矢量和测高仪测得的月心距作为观测量,采用扩展Kalman滤波估计月球探测器位置和速度的自主导航技术,并给出了数字仿真分析。
补充资料：极大扩张和极小扩张
极大扩张和极小扩张
maximal and minimal extensions
极大扩张和极小扩张匡.习的司出目.公油抽lex妇心.旧;MaKcl.Ma刀‘.oe H Mll.”M田.妇oe PaC山一Pe皿朋] 一个对称算子(s笋nr贺苗c opemtor)A的极大扩张和极小扩张分别是算子牙(A的闭包，(见闭算子(cfo“月。详mtor”)和A’(A的伴随，见伴随算子(呐。int opera.tor)).A的所有闭对称扩张都出现在它们之间.极大扩张和极小扩张相等等价于A的自伴性(见自伴算子(义休.adjoint operator))，并且是自伴扩张唯一性的必要和充分条件.A.H.J’Ior朋oB，B.c.lll户、MaR撰
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条