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基于解析矩的高斯过程滤波

Analytic Moment-Based Gaussian Process Filtering
课程网址: http://videolectures.net/icml09_diesenroth_ambg/  
主讲教师: Marc Peter Deisenroth
开课单位: 帝国理工学院
开课时间: 2009-08-26
课程语种: 英语
中文简介:
我们提出了一种基于解析矩的滤波器,用于由高斯过程建模的非线性随机动力系统。为预测值和滤波器步骤提供了期望值和协方差矩阵的精确表达式,其中在后一种情况下利用了额外的高斯假设。新过滤器不需要进一步的近似值。特别是,它避免了样本近似。我们将滤波器与各种可用的高斯滤波器进行比较,例如EKF,UKF和Ko等人最近提出的GP UKF。 (2007年)。
课程简介: We propose an analytic moment-based filter for nonlinear stochastic dynamical systems modeled by Gaussian processes. Exact expressions for the expected value and the covariance matrix are provided for both the prediction and the filter step, where an additional Gaussian assumption is exploited in the latter case. The new filter does not require further approximations. In particular, it avoids sample approximations. We compare the filter to a variety of available Gaussian filters, such as the EKF, the UKF, and the GP-UKF recently proposed by Ko et al. (2007).
关 键 词: 解析矩; 滤波器; 非线性随机动力系统
课程来源: 视频讲座网
最后编审: 2019-04-21:lxf
阅读次数: 116