助手标题  
全文文献 工具书 数字 学术定义 翻译助手 学术趋势 更多
查询帮助
意见反馈
   kalman增益 的翻译结果: 查询用时:0.534秒
图标索引 在分类学科中查询
所有学科
电信技术
更多类别查询

图标索引 历史查询
 

kalman增益
相关语句
  kalman gain
     The purpose of this paper is 1) to propose a Kalman-filtering-formula based ARMA spectral estimator capable of estimating spectra on line, 2)to consider a fast algorithm for recursively calculating the Kalman gain whose computational requirement is proportional to the order of the filter, and 3) to give a consistency theorem for this recursive estimator.
     本文从Kalman滤波的角度提出了一种ARMA谱的自适应估计法,导出了适用于ARMA模型的时间递归Kalman增益快速计算法,其计算量与滤波器的阶数成正比,并给出了些ARMA谱估计法的一致收敛性定理。
短句来源
  “kalman增益”译为未确定词的双语例句
     The designed adaptive Kalman filter thus can select appropriate fuse mode, adjust the noise intensity in the filter and prevent it from divergence, accordingly enhance the overall performance of the marine integrated navigation system.
     并通过修订滤波器内部的噪声强度和调整Kalman增益阵,保证系统工作稳定,从而增强组合系统对外部干扰的适应能力。
  相似匹配句对
     ESTIMATION OF STEADY-STATE KALMAN FILTER GAIN
     稳态Kalman滤波增益的估计
短句来源
     NEW ALGORITHMS OF STEAD STATE KALMAN FILTER GAIN
     稳态Kalman滤波器增益新算法
短句来源
     Increase the benefit: 100;
     增益:100;
     The unity gain building block
     单位增益
短句来源
     Weighted Kalman filter:Application
     加权Kalman filter:应用
查询“kalman增益”译词为用户自定义的双语例句

    我想查看译文中含有:的双语例句
例句
为了更好的帮助您理解掌握查询词或其译词在地道英语中的实际用法,我们为您准备了出自英文原文的大量英语例句,供您参考。
  kalman gain
Stable covariance propagation relationships are presented and the transformed Kalman gain is also furnished and its use in the determination of the externally updated error states is discussed.
      
Moreover, it enables a better adaptation of the Kalman gain to the actual estimation error.
      
The MEKF does not encounter singularities when computing the Kalman gain and it can estimate simultaneously the translation and rotation transformations.
      
A Kalman gain is used to determine if more weight is put on the measured contour versus the model prediction.
      
As a consequence also the Kalman gain was updated at each time step.
      
更多          


The purpose of this paper is 1) to propose a Kalman-filtering-formula based ARMA spectral estimator capable of estimating spectra on line, 2)to consider a fast algorithm for recursively calculating the Kalman gain whose computational requirement is proportional to the order of the filter, and 3) to give a consistency theorem for this recursive estimator.Compared with recently developed ARMA spectral estimation approaches--the overdeterminedequation method and the instrumental variable method, this estimator...

The purpose of this paper is 1) to propose a Kalman-filtering-formula based ARMA spectral estimator capable of estimating spectra on line, 2)to consider a fast algorithm for recursively calculating the Kalman gain whose computational requirement is proportional to the order of the filter, and 3) to give a consistency theorem for this recursive estimator.Compared with recently developed ARMA spectral estimation approaches--the overdeterminedequation method and the instrumental variable method, this estimator has advantages that the positivity of estimated spectra can be warranteed and parameters of ARMA processes can be identified in real time. Numerical examples show that this estimator provides higher resolution than AR spectral estimation.

本文从Kalman滤波的角度提出了一种ARMA谱的自适应估计法,导出了适用于ARMA模型的时间递归Kalman增益快速计算法,其计算量与滤波器的阶数成正比,并给出了些ARMA谱估计法的一致收敛性定理。较诸常用的超定方程法和辅助变量法,本方法具有能保证估计谱的正性、且能实时地识别出ARMA过程参量的优点。数值计算表明,所述方法有着良好的分辨率。

A parameter estimation algorithm for bilinear time series model which is based on Kalman filtering is proposed in this paper. To overcome the divergence of the filter, the prediction error covariance matrix is monitered, and is reset when necessary. A simulation example is given to compare this algorithm with the recursive prediction error psrameter estimator.

本文给出了一种用于双线性时间序列模型参数估计的自适应Kalman滤波器,在滤波过程中对误差协方差阵进行监控,使Kalman增益矩阵不趋于零,以保证观测数据对滤波的校正作用,并通过仿真例子将它和递推预报误差估计方法进行了比较。

A fast recursive total least squares algorithm is developed to allow recursive computation of total least squares solution for adaptive finite impulse response (FIR) filters. The augmented data vector is used as search vector for the iterative algorithm. Using the shift structure of the augmented data vector, the fast algorithm for the gain vector is given. Unlike fast algorithm of Kalman gain vector, less operations per time step is necessary, while being stable numerically. The operations for extracting the...

A fast recursive total least squares algorithm is developed to allow recursive computation of total least squares solution for adaptive finite impulse response (FIR) filters. The augmented data vector is used as search vector for the iterative algorithm. Using the shift structure of the augmented data vector, the fast algorithm for the gain vector is given. Unlike fast algorithm of Kalman gain vector, less operations per time step is necessary, while being stable numerically. The operations for extracting the smallest eigenvalue and the corresponding eigenvectors of the augmented data correlation matrix is O(N) and less than the ones of Davila′s RTLS algorithm per time step. The performance of the algorithms is evaluated via simulations.

提出了一种新的递归全局最小二乘快速算法,其可用于递归计算自适应(FIR)滤波问题的全局最小二乘(TLS)解.在这个算法中,以增广数据矢量为优化搜索方向,其快速计算归结为新定义的增益矢量的快速计算.利用数据矢量的位移结构找到了计算增益矢量的快速算法,它的运算量比Kalman增益矢量的快速算法的运算量少,且不存在数值计算不稳定性问题.在追踪与增广协方差矩阵的最小特征值相关联的特征矢量过程中,这个算法每步须O(N)乘法运算,比Davila的RTLS算法的运算量少.由计算机仿真比较了有关算法的性能

 
<< 更多相关文摘    
图标索引 相关查询

 


 
CNKI小工具
在英文学术搜索中查有关kalman增益的内容
在知识搜索中查有关kalman增益的内容
在数字搜索中查有关kalman增益的内容
在概念知识元中查有关kalman增益的内容
在学术趋势中查有关kalman增益的内容
 
 

CNKI主页设CNKI翻译助手为主页 | 收藏CNKI翻译助手 | 广告服务 | 英文学术搜索
版权图标  2008 CNKI-中国知网
京ICP证040431号 互联网出版许可证 新出网证(京)字008号
北京市公安局海淀分局 备案号:110 1081725
版权图标 2008中国知网(cnki) 中国学术期刊(光盘版)电子杂志社