A method is advanced to avoid of filter diffusion by using residual error prediction.
提出一种基于预报残差方法来检测滤波发散问题。
The order of synthesis filter is fixed in multi-pulse excited linear prediction coding(MPLPC) method.
多脉冲激励线性预测编码（MPLPC）方法中，合成滤波器的阶数是固定的。
The results show that in the simulation of non-linear system model, this framework for Bayesian predictive filter can implement the tracking of simple motion and the orientation prediction.
实验结果表明，在非线性系统模型的仿真中，贝叶斯预测滤波框架能够较好的实现对简单物体运动的跟踪和方位的预测。
An inverse stochastic boundary element method for prediction of contact stress is presented by combining improved filter algorithm with stochastic boundary element method.
将改进的滤波算法和随机边界元法结合，提出了用于预测接触应力的逆随机边界元法。
This paper presents an adaptive fault prediction method based on strong tracking filter, which can predict faults in a class of nonlinear time varying systems.
本文提出了一种基于强跟踪滤波器的自适应故障预报方法，能够对一类带时变参数的非线性系统进行故障预报。
This paper introduces and analyzes the application of the least square method and Kalman filter in time prediction.
介绍和分析了最小二乘和卡尔曼滤波方法在时间预报中的应用。
This paper presents a hybrid model for urban arterial travel time prediction based on the so-called state space neural networks (SSNN) and the extended Kalman Filter (EKF).
提出了一种基于状态空间神经网络(SSNN)和拓展卡尔曼滤波(ekf)的混合式行程时间预测模型。
This paper studies an adaptive filter with adaptive prediction pre-processing in the primary input.
本文研究了一种对当输入端进行自适应预测预处理的自适应滤波器。
Using smoothing filter and average-force algorithm to position beacon's facula, then use kalman prediction algorithm with the adaptive capacity to achieve the recursive tracking algorithm.
以平均值平滑滤波法和质心法实现了对信标光斑定位，利用卡尔曼预测算法实现了具有自适应能力的递归跟踪算法。
Using the MATLAB, this paper introduces an application in harmonics and reactive-current compensation for an active filter system, which based on the adaptive simulink in signal prediction.
本设计运用MATLAB语言实现信号预测模型的自适应仿真在有源滤波系统的谐波和无功电流补偿中的应用。
A small target detection method using Kalman filter as the clutter background prediction was presented.
提出了一种采用卡尔曼滤波器作为杂波背景预测器的小目标检测方法。
The desired filter can be constructed by using the cross-cut and geometry method. The optimum prediction of the state vector is also given.
通过运用斜割支线和几何方法，给出状态向量的卡尔曼滤波与最优预测。
As for the target's track prediction, this paper USES the particle filter tracking algorithm.
而对于目标运动轨迹的预测，本文采用粒子滤波跟踪算法。
The on-board autonomous term orbit prediction is built according to epoch state filter. And sun-synchronous orbit satellites are taken as examples for the simulation.
采用历元状态滤波建立了星上自主中长期轨道预报方法，并以太阳同步轨道卫星为例对算法进行了仿真验证。
By combining the motion state equation with the Kalman filter algorithm, a mathematic calculation method for accurate prediction of the polished rod speed of the pumping unit is worked out.
把抽油机运动状态方程和卡尔曼滤波算法相结合，构造了一套适用的精确预测抽油机悬点速度的数学算法。
In the part of tracking, combining the improved Mean-Shift algorithm and Kalman filter prediction.
在跟踪部分，采用改进的均值漂移算法和卡尔曼滤波预测结合。
A new algorithm for adaptive prediction error filter is presented.
本文提出一种自适应预测滤波器的新算法。
Finally, some solutions to improve prediction accuracy of the tracking filter are given.
最后给出了提高滤波预测精度的一些解决方法。
A new approach to FMCW radar detection of velocity deception jamming based on adaptive linear prediction error filter is described in this paper.
针对调频连续波(FMCW)雷达，提出了采用自适应线性预测滤波预处理实现速度欺骗干扰的检测。
An adaptive routing based on Kalman filter prediction theory for DTMSN was raised.
提出了一种基于卡尔曼滤波器预测理论的容延迟移动传感器网络路由协议。
In an extreme case, when the aliasing effects are very severe, using wiener filter can reduce the prediction errors'energy by about 50% in comparison with using the ideal low pass filter.
极限情况下，当混叠十分严重时，相对于理想低通滤波器，用维纳滤波器进行亚象素插值能将预测残差均方和减少一半。
Through background subtraction to achieve target detection, and then output the results to the Kalman filter, prediction next appear (red), can occur and the actual position (green) compared.
它通过背景相减实现目标检测，然后把输出的结果交给Kalman滤波器，预测出下一出现的位置(红色)，可以和实际出现的位置(绿色)相比较。
Through background subtraction to achieve target detection, and then output the results to the Kalman filter, prediction next appear (red), can occur and the actual position (green) compared.
它通过背景相减实现目标检测，然后把输出的结果交给Kalman滤波器，预测出下一出现的位置(红色)，可以和实际出现的位置(绿色)相比较。
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