NDLI: Fixed-lag Minimum Variance FIR Smoothers for Continuous-time Systems

Content Provider	IEEE Xplore Digital Library
Author	Bo Kyu Kwon Soohee Han Wook Hyun Kwon
Copyright Year	2006
Description	Author affiliation: Sch. of Electr. Eng. & Comput. Sci., Seoul Nat. Univ. (Bo Kyu Kwon; Soohee Han; Wook Hyun Kwon)
Abstract	In this paper, we consider the fixed-lag finite impulse response (FIR) smoother problem for a class of continuous-time systems. The proposed fixed-lag FIR smoother is represented linearly with inputs and outputs on the recent time interval, and has coefficients without respect to any state information. It is optimal in view of the minimum variance performance criterion with unbiased constraints. The approach to the minimum variance fixed-lag FIR (MVF) smoother provides a closed-form solution and can be easily extended to an FIR filter by setting a lag size to zero. A simulation example is presented to validate the effectiveness of the proposed approach by comparing to a traditional fixed-lag Kalman smoother
Starting Page	765
Ending Page	769
File Size	4801604
Page Count	5
File Format	PDF
ISBN	8995003847
DOI	10.1109/SICE.2006.315270
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-10-18
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	The Institute of Control, Automation and Systems
Subject Keyword	Finite impulse response filter IIR filters State estimation Smoothing methods Time measurement Information filtering Information filters Covariance matrix Computer science Closed-form solution Receding horizon strategy Minimum variance FIR smoother Unbiasedness property
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Minimum Variance FIR Smoothers for Discrete-Time State Space Models

Minimum Variance FIR Smoothers for Continuous-Time State Space Signal Models

A Low-Complexity Sliding-Window Kalman FIR Smoother for Discrete-Time Models

A Receding Horizon Kalman FIR Filter for Linear Continuous-Time Systems (1999)

Novel Unbiased Optimal Receding-Horizon Fixed-Lag Smoothers for Linear Discrete Time-Varying Systems

An Optimal Receding Horizon FIR Filter for Continuous-Time Linear Systems

A receding horizon Kalman filter with the estimated initial state on the horizon

A Best Lag Size of Minimum Variance FIR Smoothers

Derivation of a stable recursive form of FIR filter/FIR smoother

Fixed-lag Minimum Variance FIR Smoothers for Continuous-time Systems

Similar Documents

Minimum Variance FIR Smoothers for Discrete-Time State Space Models

Minimum Variance FIR Smoothers for Continuous-Time State Space Signal Models

A Low-Complexity Sliding-Window Kalman FIR Smoother for Discrete-Time Models

A Receding Horizon Kalman FIR Filter for Linear Continuous-Time Systems (1999)

Novel Unbiased Optimal Receding-Horizon Fixed-Lag Smoothers for Linear Discrete Time-Varying Systems

An Optimal Receding Horizon FIR Filter for Continuous-Time Linear Systems

A receding horizon Kalman filter with the estimated initial state on the horizon

A Best Lag Size of Minimum Variance FIR Smoothers

Derivation of a stable recursive form of FIR filter/FIR smoother

Fixed-lag Minimum Variance FIR Smoothers for Continuous-time Systems