贝叶斯滤波,Bayesian filtering
1)Bayesian filtering贝叶斯滤波
1.Aiming at the problem of targe tracking inBayesian filtering process,some typicalBayesian filtering methods such as EKF,UKF,PF and UPF are proposed.针对贝叶斯滤波过程中存在的目标跟踪问题,提出几种典型的贝叶斯滤波方法,如EKF,UKF,PF和UPF等,基于这些方法所构建的框架,对它们进行性能测试和比较,并在非线性环境下,讨论这些方法的特点,仿真实验结果表明,在非线性非高斯环境下,UPF方法的性能是最优的。
英文短句/例句
1.A Introduction to the Projection Filter with Application to Bayes Filtering Problem投影滤波器原理在贝叶斯滤波中的应用
2.Target Tracking Based on Bayesian Filter in Colored Image Sequence;彩色图象序列中基于贝叶斯滤波的目标跟踪
3.Filter Algorithm of Bayesian State Estimation Using Piecewise Constant基于分段常值的贝叶斯状态估计滤波算法
4.Application of Particle Filter in the Bayesian Dynamic Models;粒子滤波算法在贝叶斯动态模型中的应用
5.Based on Bayesian statistics and the robust estimation principle.基于贝叶斯统计和抗差估计原理,我们构造了一种抗差滤波算法。
6.Particle Filter for Dynamic Bayesian Networks Inference Based on BK Algorithm动态贝叶斯网络的一种基于BK的粒子滤波推理算法
7.Study on Spam Filtering Technology Based Bayes;基于贝叶斯算法的垃圾邮件过滤研究
8.Spam Filtering Optimization Algorithm Based on Bayes;基于贝叶斯的垃圾邮件过滤优化算法
9.Collaborative filtering recommendation algorithm based on Bayesian theory基于贝叶斯理论的协同过滤推荐算法
10.Improved Nave Bayesian spam filtering algorithm改进的朴素贝叶斯垃圾邮件过滤算法
11.Research of Mail Filtering Based on Bayesian Incremental Classification基于贝叶斯增量分类的邮件过滤研究
12.There are two kinds of filters that come near to this ideal currently: Bayesian Filters and Community Filters.有两种过滤接近这个理想目前:贝叶斯过滤器、过滤社区.
13.Flight delay propagation research based on Bayesian net;基于贝叶斯网络的航班延误波及研究
14.Bayesian face recognition using Gabor transform融合Gabor小波和贝叶斯的人脸识别算法
15.Bayesian face recognition using wavelet transform and 2DPCA融合小波与2D PCA的贝叶斯人脸识别
16.Research on Spam Filtering System Based on Na(?)ve Bayes Algorithm;基于朴素贝叶斯算法的垃圾邮件过滤系统研究
17.Research of Chinese Spam Filtering Algorithm Based on Bayes Theory基于贝叶斯理论的中文垃圾邮件过滤算法研究
18.Personalized Spam Filtering Based on Naive Bayes Algorithm基于朴素贝叶斯算法的个性化垃圾邮件过滤
相关短句/例句
Bayes filter贝叶斯滤波
3)Bayesian filter贝叶斯滤波
4)Bayesian filter theory贝叶斯滤波理论
1.To solve localization problems of autonomous robots,self-localization methods based onBayesian filter theory are investigated.针对自主机器人定位问题,研究了基于贝叶斯滤波理论的自定位方法。
5)Extended Bayesian filter扩展贝叶斯滤波
6)Bayesian methods贝叶斯滤波原理
延伸阅读
贝叶斯公式贝叶斯公式为利用搜集到的信息对原有判断进行修正提供了有效手段。在采样之前,经济主体对各种假设有一个判断(先验概率),设为,{}。关于先验概率的分布,通常可根据经济主体的经验判断确定(当无任何信息时,一般假设各先验概率相同),较复杂精确的可利用包括最大熵技术或边际分布密度以及相互信息原理等方法来确定先验概率分布。当采样得到样本值后,当事人对各假设的判断(后验概率)为 ,= 1, 2, %26#8230;, (5.5)在实际经济生活中,信息搜寻工作不是一次就完成的。当信息搜寻进行到某一阶段,设已进行了 次采样( =1,2,%26#8230;),此时经济主体对各假设的后验概率的认识为 =1, 2, %26#8230;, (5.6) 其中,表示在第次采样前对假设的判断,当 =1时即表示第一次采样前的先验概率,从而式(5.5)变成式(5.6)的一个特例,即,将其记为。