The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
A new sampling method in particle filter based on Pearson correlation coefficient
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Citations
Cites
Novel approach to nonlinear/non-Gaussian Bayesian state estimation
Gordon, N. J., Salmond, D. J., & Smith, A. F. M. (1993) · IEE Proceedings F Radar and Signal Processing · doi:10.1049/ip-f-2.1993.0015 · Cited by 7,550
Unscented Filtering and Nonlinear Estimation
Julier, S. J., & Uhlmann, J. K. (2004) · Proceedings of the IEEE · doi:10.1109/jproc.2003.823141 · Cited by 6,588
Thirteen Ways to Look at the Correlation Coefficient
Lee Rodgers, J., & Nicewander, W. A. (1988) · The American Statistician · doi:10.1080/00031305.1988.10475524 · Cited by 4,052
Monte Carlo Filter and Smoother for Non-Gaussian Nonlinear State Space Models
Kitagawa, G. (1996) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.1996.10474692 · Cited by 2,404
Sequential Monte Carlo Methods for Dynamic Systems
Liu, J. S., & Chen, R. (1998) · Journal of the American Statistical Association · doi:10.1080/01621459.1998.10473765 · Cited by 2,191
Stochastic stability of the discrete-time extended Kalman filter
Reif, K., Gunther, S., Yaz, E., & Unbehauen, R. (1999) · IEEE Transactions on Automatic Control · doi:10.1109/9.754809 · Cited by 1,011
Improved particle filter for nonlinearproblems
Carpenter, J., Clifford, P., & Fearnhead, P. (1999) · IEE Proceedings - Radar, Sonar and Navigation · doi:10.1049/ip-rsn:19990255 · Cited by 996
A survey of convergence results on particle filtering methods for practitioners
Crisan, D., & Doucet, A. (2002) · IEEE Transactions on Signal Processing · doi:10.1109/78.984773 · Cited by 919
Effective use of Pearson's product–moment correlation coefficient
Puth, M.-T., Neuhäuser, M., & Ruxton, G. D. (2014) · Animal Behaviour · doi:10.1016/j.anbehav.2014.05.003 · Cited by 446
Ye, J. (2014) · Applied Mathematical Modelling · doi:10.1016/j.apm.2013.07.010 · Cited by 200
Cited by
Frick, N. R. J., Mirbabaie, M., Stieglitz, S., & Salomon, J. (2021) · Journal of Decision Systems · doi:10.1080/12460125.2020.1870065 · Cited by 138
Metadata
- Authors
- Zhou, H., Deng, Z., Xia, Y., & Fu, M.
- Venue
- Neurocomputing
- Publisher
- Elsevier BV
- Published
- 2016-12
- Volume
- 216
- Pages
- 208-215
- ISSN
- 0925-2312 (ISSN-L)
- OpenAlex
- W2494454509
- Cited by
- 417
- References
- 15
- FWCI
- 21.85
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Zhou, H., Deng, Z., Xia, Y., & Fu, M. (2016). A new sampling method in particle filter based on Pearson correlation coefficient. Neurocomputing. https://doi.org/10.1016/j.neucom.2016.07.036
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
