Identification of HIV Dynamic System in the Case of Incomplete Experimental Data
Keywords:Inverse problem, least square methods, parameter estimation, HIV model, incomplete data.
AbstractIn this paper we apply an inverse method that estimates parameters of deterministic mathematical models to an HIV model. We consider the case where experimental data concerning the values of some variables is incomplete or unknown. The objective is to estimate the parameters and to restore the information concerning the behaviour of the incomplete data. The method is based on integrating both sides of equations of a dynamic system, and applying some minimization methods (for example least square method). Such an approach was first suggested in  and . Analysis of the HIV model and corresponding numerical example is presented.
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