南方科技大学知识苑(SUSTech KC): Auxiliary two-filter particle smoothing for one generalized hidden Markov model

题名	Auxiliary two-filter particle smoothing for one generalized hidden Markov model
作者	Chen, Yunqi1 ; Yan, Zhibin 2; Zhang, Xing 3
通讯作者	Chen, Yunqi
发表日期	2024-06-01
DOI	10.1016/j.isatra.2024.04.009
发表期刊	ISA TRANSACTIONS 影响因子和分区
ISSN	0019-0578
EISSN	1879-2022
卷号	149
摘要	This paper develops two -filter particle smoothing (TFPS) algorithms for the nonlinear fixed -interval smoothing problem of one generalized hidden Markov model (GHMM), where the current observation depends not only on the current state, but also on one-step previous state. Firstly, by Bayesian approach, the two -filter smoothing (TFS) formula for GHMM is established to calculate smoothing densities. In this TFS formula, the backward information prediction density is generally not a density of the state. This results in a difficulty that the normal sequential Monte Carlo (SMC) sampling technique cannot be directly applied to design corresponding TFPS algorithms based on the TFS formula. To solve this difficulty, a generalized TFS formula for GHMM is then proposed by introducing a sequence of artificial densities. By combining this generalized TFS formula, SMC, and the auxiliary variable sampling technique, a basic auxiliary TFPS (ATFPS) algorithm with quadratic computational complexity is proposed, and a simplified ATFPS algorithm with linear computational complexity is further developed. Finally, the effectiveness and superiority of the two proposed ATFPS algorithms for GHMM are verified via simulation examples and real experimental data.
关键词	Particle smoothing Two-filter smoothing Auxiliary variable sampling Hidden Markov model Sequential Monte Carlo
相关链接	[来源记录]
收录类别	SCI ; EI
语种	英语
学校署名	第一 ; 通讯
资助项目	Shenzhen Science and Technology Inno-vation Commission[JCYJ20190806 143607340]
WOS研究方向	Automation & Control Systems ; Engineering ; Instruments & Instrumentation
WOS类目	Automation & Control Systems ; Engineering, Multidisciplinary ; Instruments & Instrumentation
WOS记录号	WOS:001249631700001
出版者	ELSEVIER SCIENCE INC
ESI学科分类	ENGINEERING
来源库	Web of Science
引用统计
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/787722
专题	南方科技大学
作者单位	1.Southern Univ Sci & Technol, Shenzhen Key Lab Control Theory & Intelligent Syst, Shenzhen 518055, Peoples R China 2.Harbin Inst Technol Shenzhen, Sch Sci, Shenzhen 518055, Peoples R China 3.Guangxi Univ, Sch Math & Informat Sci, Nanning 530004, Peoples R China
第一作者单位	南方科技大学
通讯作者单位	南方科技大学
第一作者的第一单位	南方科技大学
推荐引用方式 GB/T 7714	Chen, Yunqi,Yan, Zhibin,Zhang, Xing. Auxiliary two-filter particle smoothing for one generalized hidden Markov model[J]. ISA TRANSACTIONS,2024,149.
APA	Chen, Yunqi,Yan, Zhibin,&Zhang, Xing.(2024).Auxiliary two-filter particle smoothing for one generalized hidden Markov model.ISA TRANSACTIONS,149.
MLA	Chen, Yunqi,et al."Auxiliary two-filter particle smoothing for one generalized hidden Markov model".ISA TRANSACTIONS 149(2024).