1) Kalman optimal prediction equation
Kalman最优预测方程
2) optimal estimation equation
最优估测方程
3) optimal prediction
最优预测
1.
To the widely existed characteristics of time-delay,non-linear and timevarying of parameters in the industry process,an adaptive neuron-fuzzy PID controller based on optimal prediction is presented.
针对工业过程中普遍存在的时滞、非线性、对象参数时变等特性,提出了一种基于最优预测的神经元模糊自整定PID控制算法。
2.
One is to derive the optimal prediction and the other is to find its necessary and sufficient conditions.
对于给定的一个可预测变量，需要解决两个问题：一是求出最优预测，二是找出其存在最优预测的充要条件。
4) best prediction
最优预测
1.
This paper explores the application of conditional expectation in solutions to mathematical expectation and best prediction.
条件数学期望是概率论中一个重要概念,本文通过求数学期望的例子和最优预测探讨了它的应用。
5) optimal predication
最优预测
1.
Considering the double-star positioning system s characteristic of using two geostationary satellites to determine the user s position actively and delayed position information, this paper put forward an optimal predication model of double-star position /SINS (Strap-down Inertial Navigation System) integrated system.
针对双星定位系统采用两颗地球同步卫星进行有源定位和存在定位位置滞后的特点,提出了双星定位/捷联惯性导航系统(SINS)组合的最优预测模型。
2.
According to the characteristic of Beidou double-star positing system(double-star positoin),this paper puts forward the optimal predication model of double-star position/SINS integrated system.
根据北斗双星定位系统(简称双星定位)的特点,提出了北斗双星与SINS组合的最优预测模型。
6) Kalman predictor
Kalman预测器
1.
In lane tracking,the Region of Interest(ROI) is established using parameters predicted through the Kalman predictor.
车道线跟踪利用Kalman预测参数建立感兴趣区域,然后用扫描线法搜索车道线边界点,在车道线间断区域利用Kalman预测器定位车道线边界。
2.
In lane tracking,the region of interest(ROI) was established with parameters predicted through the Kalman predictor,the lane boundary points were searched by scanning line method in ROI,and the lane boundary in discontinuous area was located by Kalman predictor.
提出了一种针对高速公路的车道线检测与跟踪方法;在图像预处理中采用基于采样的自适应阈值以满足不同光照条件下的使用要求,采用霍夫变换(HT,Hough Transform)进行车道线初始检测,车道线跟踪利用Kalman预测参数动态建立感兴趣区域(ROI,Region of Interest),用扫描线法搜索车道线边界点,在车道线间断区域利用Kalman预测器定位车道线边界;设计了一个失效判别模块,验证跟踪结果,当跟踪失败时,重新启动初始检测算法进行识别;实验结果表明,对于不同的车道线种类和在大部分车道线被前方车辆遮挡的条件下,该算法均具有较高的实时性和鲁棒性。
补充资料：发育进度预测法(见发生期预测)
发育进度预测法(见发生期预测)
发育进度预测法见发生期预测。
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