1) stationary gaussian markovian process 平稳高斯 马尔可夫过程2) Gauss-Markov process 高斯-马尔科夫过程 1. The autonomous optical navigation algorithm for spacecraft around Moon using the Gauss-Markov process and Unscented Kalman filter is presented. 提出了一种利用高斯-马尔科夫过程和Unscented卡尔曼...
TL; DR Kalman filters and smoothers can be viewed as solvers for a family of Gaussian process regression models, in particular, Markov Gaussian processes. Say, for example, we have a GP regression model U(t)Yk∼GP(0,C(t,t′)),=U(tk)+ξk,(1) Now, what is the goal of GP regre...
mean stationaryGaussian processes, $Y(t), ~t \\\in eals$ with $k$ derivatives, for which \\\begin{equation} Z(t) \\\equiv (Y^{(0)}(t), Y^{(1)}(t), \\\ldots, Y^{(k)}(t) ), ~t \\\ge 0 \\\end{equation} oindent is a $(k+1)$-vector Markov process. (here,...
bringing the reader to the heart of contemporary research. It presents the remarkable isomorphism theorems of Dynkin and Eisenbaum and then shows how they can be applied to obtain new properties of Markov processes by using well-established techniques in Gaussian process theory. This original, readab...
A homogeneous Gaussian Markov lattice-process model has a regression coefficient that determines the extent to which a random variable of a vertex is dependent on those of the neighbors. In many studies, the absolute value of this parameter has been assumed to be less than the reciprocal of the...
(1961). Estimation of the parameters of a stationary Gaussian Markov process. Dokl. Akad. Nauk SSSR 145, 13-16.M. Arato. Estimation of the parameters of a stationary gaussian markov process. Dokl. Akad. Nauk SSSR, 145:1316, 1961.
GAUSSIAN PROCESS ノ MARKOVセイ ノ テイギ ニ カンスル ヒトツ ノ チュウイ タジュウ マルコフセイ ト ヨソク リロン エノ オウヨウ主要由井原 俊輔编写,在1972年被收录,
随机过程的定义是:参数集向同一个可测空间上随机变量的映射. 一般参数集会被赋予时间的含义,但是也可以是更高维的R^n空间. 这些随机变量之间不一定独立,比如Markov过程,要求随机变量之间的依赖是短时/局域的 (类似MD轨迹分析中一个变量自相关系性是短时的). Gaussian过程要求对任意个参数x1:n,其对应的随机变量y1...
GaussianMarkovRandomFieldModels OutlineI Introduction Why? Definition WhatisaGMRF? Theprecisionmatrix DefinitionofaGMRF Example:Auto-regressiveprocess WhyareGMRFsimportant? MainfeaturesofGMRFs PropertiesofGMRFs InterpretationofelementsofQ Markovproperties ...
Classifying human hand gestures in the context of a Sign Language has been historically dominated by Artificial Neural Networks and Hidden Markov Model wit... N Gamage,CK Ye,R Akmeliawati,... - 《Pattern Recognition Letters》 被引量: 40发表: 2011年 Gaussian process dynamical models for nonpara...