Abstract
The HIV (Human Immunodeficiency Virus) causes AIDS (Acquired Immune Deficiency Syndrome). The process of infection and mutation by HIV can be described by a 3rd order state equation. For this HIV model that includes the dynamics of the mutant virus, we present a parameter estimation scheme using two state variables sporadically measured, out of the three, by employing a genetic algorithm. It is assumed that these non-uniformly sampled measurements are subject to random noises. The effectiveness of the proposed parameter estimation is demonstrated by simulations. In addition, the estimated parameters are used to analyze the equilibrium points of the HIV model, and the results are shown to be consistent with those previously obtained.
| Original language | English |
|---|---|
| Pages (from-to) | 753-759 |
| Number of pages | 7 |
| Journal | Journal of Institute of Control, Robotics and Systems |
| Volume | 17 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 2011 Aug 1 |
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Keywords
- Genetic algorithm
- HIV model
- Mutant virus
- Non-uniformly sampled output data
- Parameter estimation
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Applied Mathematics
Cite this
Parameter estimation of an hiv model with mutants using sporadically sampled data. / Kim, Seok Kyoon; Kim, Jung Su; Yoon, Tae Woong.
In: Journal of Institute of Control, Robotics and Systems, Vol. 17, No. 8, 01.08.2011, p. 753-759.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Parameter estimation of an hiv model with mutants using sporadically sampled data
AU - Kim, Seok Kyoon
AU - Kim, Jung Su
AU - Yoon, Tae Woong
PY - 2011/8/1
Y1 - 2011/8/1
N2 - The HIV (Human Immunodeficiency Virus) causes AIDS (Acquired Immune Deficiency Syndrome). The process of infection and mutation by HIV can be described by a 3rd order state equation. For this HIV model that includes the dynamics of the mutant virus, we present a parameter estimation scheme using two state variables sporadically measured, out of the three, by employing a genetic algorithm. It is assumed that these non-uniformly sampled measurements are subject to random noises. The effectiveness of the proposed parameter estimation is demonstrated by simulations. In addition, the estimated parameters are used to analyze the equilibrium points of the HIV model, and the results are shown to be consistent with those previously obtained.
AB - The HIV (Human Immunodeficiency Virus) causes AIDS (Acquired Immune Deficiency Syndrome). The process of infection and mutation by HIV can be described by a 3rd order state equation. For this HIV model that includes the dynamics of the mutant virus, we present a parameter estimation scheme using two state variables sporadically measured, out of the three, by employing a genetic algorithm. It is assumed that these non-uniformly sampled measurements are subject to random noises. The effectiveness of the proposed parameter estimation is demonstrated by simulations. In addition, the estimated parameters are used to analyze the equilibrium points of the HIV model, and the results are shown to be consistent with those previously obtained.
KW - Genetic algorithm
KW - HIV model
KW - Mutant virus
KW - Non-uniformly sampled output data
KW - Parameter estimation
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UR - http://www.scopus.com/inward/citedby.url?scp=84861211118&partnerID=8YFLogxK
U2 - 10.5302/J.ICROS.2011.17.8.753
DO - 10.5302/J.ICROS.2011.17.8.753
M3 - Article
VL - 17
SP - 753
EP - 759
JO - Journal of Institute of Control, Robotics and Systems
JF - Journal of Institute of Control, Robotics and Systems
SN - 1976-5622
IS - 8
ER -