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1)  iterated Kalman filtering
迭代Kalman滤波
2)  iterated unscented Kalman filter
迭代无迹Kalman滤波
1.
Here,an iterated unscented Kalman filter was used to generate the initial particle distribution for the particle filter.
该文用迭代无迹Kalman滤波产生粒子滤波的建议分布,提出了一种新的粒子滤波算法——迭代无迹Kalman粒子滤波。
3)  iterated extend Kalman filter
迭代扩展Kalman滤波
4)  iterative filtering
迭代滤波
1.
A SAR image nonlinear iterative filtering approach based on correlated neighborhood model is presented,it can restrain error accumulation.
提出一种基于相关邻域模型可抑制误差积累的SAR图像非线性迭代滤波方法。
5)  iterative inverse filtering
迭代逆滤波
1.
An iterative inverse filtering algorithm(ITIF)is used for estimating and updating theunknown input with the orthogonal sub-space method applied later for system identification.
研究了输入未知时,根据系统运行实测响应数据识别系统结构,采用迭代逆滤波算法,用高阶AR模型对输入信号进行估计,以便最终识别系统;在模型识别中采用了正交子空间法,这一方法将正交化引入时间序列,从而实现系统阶次的自动估计及模型识别。
6)  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。
补充资料:层层迭迭
1.见"层层迭迭"。
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