A comparison of nonlinear filtering approaches in the context of anHIV model
In this paper three different filtering methods, the ExtendedKalman Filter (EKF), the Gauss-Hermite Filter (GHF), and theUnscented Kalman Filter (UKF), are compared for state-only andcoupled state and parameter estimation when used with log statevariables of a model of the immunologic response to th...
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| Format: | Article |
| Language: | English |
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AIMS Press
2010-03-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2010.7.213 |
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| author | H. Thomas Banks Shuhua Hu Zackary R. Kenz Hien T. Tran |
| author_facet | H. Thomas Banks Shuhua Hu Zackary R. Kenz Hien T. Tran |
| author_sort | H. Thomas Banks |
| collection | DOAJ |
| description | In this paper three different filtering methods, the ExtendedKalman Filter (EKF), the Gauss-Hermite Filter (GHF), and theUnscented Kalman Filter (UKF), are compared for state-only andcoupled state and parameter estimation when used with log statevariables of a model of the immunologic response to the humanimmunodeficiency virus (HIV) in individuals. The filters areimplemented to estimate model states as well as model parametersfrom simulated noisy data, and are compared in terms of estimationaccuracy and computational time. Numerical experiments reveal thatthe GHF is the most computationally expensive algorithm, while theEKF is the least expensive one. In addition, computationalexperiments suggest that there is little difference in theestimation accuracy between the UKF and GHF. When measurements aretaken as frequently as every week to two weeks, the EKF is thesuperior filter. When measurements are further apart, the UKF is thebest choice in the problem under investigation. |
| format | Article |
| id | doaj-art-98d1303868594b40a0a87b5a7d0a963a |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2010-03-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-98d1303868594b40a0a87b5a7d0a963a2025-01-24T02:00:28ZengAIMS PressMathematical Biosciences and Engineering1551-00182010-03-017221323610.3934/mbe.2010.7.213A comparison of nonlinear filtering approaches in the context of anHIV modelH. Thomas Banks0Shuhua Hu1Zackary R. Kenz2Hien T. Tran3Center for Research in Scientific Computation, Raleigh, NC 27695-8205Center for Research in Scientific Computation, Raleigh, NC 27695-8205Center for Research in Scientific Computation, Raleigh, NC 27695-8205Center for Research in Scientific Computation, Raleigh, NC 27695-8205In this paper three different filtering methods, the ExtendedKalman Filter (EKF), the Gauss-Hermite Filter (GHF), and theUnscented Kalman Filter (UKF), are compared for state-only andcoupled state and parameter estimation when used with log statevariables of a model of the immunologic response to the humanimmunodeficiency virus (HIV) in individuals. The filters areimplemented to estimate model states as well as model parametersfrom simulated noisy data, and are compared in terms of estimationaccuracy and computational time. Numerical experiments reveal thatthe GHF is the most computationally expensive algorithm, while theEKF is the least expensive one. In addition, computationalexperiments suggest that there is little difference in theestimation accuracy between the UKF and GHF. When measurements aretaken as frequently as every week to two weeks, the EKF is thesuperior filter. When measurements are further apart, the UKF is thebest choice in the problem under investigation.https://www.aimspress.com/article/doi/10.3934/mbe.2010.7.213hiv.gauss-hermite filterunscented kalman filterextended kalman filter |
| spellingShingle | H. Thomas Banks Shuhua Hu Zackary R. Kenz Hien T. Tran A comparison of nonlinear filtering approaches in the context of anHIV model Mathematical Biosciences and Engineering hiv. gauss-hermite filter unscented kalman filter extended kalman filter |
| title | A comparison of nonlinear filtering approaches in the context of anHIV model |
| title_full | A comparison of nonlinear filtering approaches in the context of anHIV model |
| title_fullStr | A comparison of nonlinear filtering approaches in the context of anHIV model |
| title_full_unstemmed | A comparison of nonlinear filtering approaches in the context of anHIV model |
| title_short | A comparison of nonlinear filtering approaches in the context of anHIV model |
| title_sort | comparison of nonlinear filtering approaches in the context of anhiv model |
| topic | hiv. gauss-hermite filter unscented kalman filter extended kalman filter |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2010.7.213 |
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