Particle Flow Filters: Biases and Bias Avoidance-Reference-Cited by-同舟云学术

Particle Flow Filters: Biases and Bias Avoidance

Published:2019-07 Issue: Volume: Page:
ISSN:
Container-title:2019 22th International Conference on Information Fusion (FUSION)
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Author:

Crouse David Frederic¹

Affiliation:

1. Naval Research Laboratory,Washington,DC,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8977236/9011156/09011266.pdf?arnumber=9011266

Reference64 articles.

1. New Theory and Numerical Results for Gromov's Method for Stochastic Particle Flow Filters

2. Generalized Gromov method for stochastic particle flow filters;daum;Proceedings of SPIE Signal Processing Sensor/Information Fusion and Target Recognition XXVI,2017

3. Renormalization group flow in K-space for nonlinear filters, Bayesian decisions and transport;daum;Proc of International Conference on Information Fusion[C],2015

4. Proof that particle flow corresponds to Bayes' rule: Necessary and sufficient conditions;daum;Proceedings of SPIE Signal Processing Sensor/Information Fusion and Target Recognition XXIV,2015

5. A baker's dozen of new particle flows for nonlinear filters Bayesian decisions and transport;daum;Proceedings of SPIE Signal Processing Sensor Fusion and Target Recognition XXIV,2015

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