General convergence result for continuous-discrete feedback particle filter-Reference-Cited by-同舟云学术

General convergence result for continuous-discrete feedback particle filter

Published:2021-07-12 Issue: Volume: Page:1-15
ISSN:0020-7179
Container-title:International Journal of Control
language:en
Short-container-title:International Journal of Control

Author:

Chen Xiuqiong¹²,Luo Xue³,Shi Ji⁴,Yau Stephen S.-T.⁵⁶

Affiliation:

1. Yau Mathematical Sciences Center, Tsinghua University, Beijing, People's Republic of China

2. School of Mathematics, Renmin University of China, Beijing, People's Republic of China

3. Key Laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB) and School of Mathematical Sciences, Beihang University (Shahe campus), Beijing, People's Republic of China

4. Beijing Advanced Innovation Center for Imaging Theory and Technology, Academy for Multidisciplinary Studies, Capital Normal University, Beijing, People's Republic of China

5. Department of Mathematical Sciences, Tsinghua University, Beijing, People's Republic of China

6. Yanqi Lake Beijing Institute of Mathematical Sciences and Applications (BIMSA), Huairou, Beijing, People's Republic of ChinaDedicate to Professor Peter Caines on the occasion of his 75th birthday

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Tsinghua University

Tsinghua University Education Foundation fund

Publisher

Informa UK Limited

Subject

Computer Science Applications,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207179.2021.1948105

Reference30 articles.

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2. Berntorp, K. (2015). Feedback particle filter: application and evaluation. In 2015 18th International Conference on Information Fusion (Fusion) (pp. 1633–1640). IEEE.

3. Berntorp, K. (2018). Comparison of gain function approximation methods in the feedback particle filter. In 2018 21st International Conference on Information Fusion (Fusion) (pp. 123–130). IEEE.

4. CAPABILITY MEASURES FOR m -DEPENDENT STATIONARY PROCESSES

5. Real-Time Solution of Time-Varying Yau Filtering Problems via Direct Method and Gaussian Approximation

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