山东理工大学学报（自然科学版）Issue(1)：52-57,6.
基于近似贝叶斯计算的HMM隐状态估计
Estimation of hidden state of HMM based on approximate bayesian compute
陈琦 1胡锡健1
作者信息
- 1. 新疆大学数学与系统科学学院，新疆乌鲁木齐830046
- 折叠
摘要
Abstract
In order to obtain the estimation of HMM's hidden state when the likelihood function of HMM is not analytically available ,we view the estimation of HMM's hidden state as a bayesian optimal filtering problem ,and adopt the particle filter algorithm based on approximate Bayesian computation to resolve such problem .As a result ,we solve the filtering problem which likelihood function is not analytically available and some of other methods like the Kalman filter or extend Kalman filtering and particle filter can't solve .关键词
隐状态/贝叶斯估计/粒子滤波/近似贝叶斯计算Key words
hidden state/Bayesian estimate/particle filter/approximate Bayesian compute分类
数理科学引用本文复制引用
陈琦,胡锡健..基于近似贝叶斯计算的HMM隐状态估计[J].山东理工大学学报（自然科学版）,2014,(1):52-57,6.
