System identification: theory for the user
System identification: theory for the user
Some new trends in identification and modeling of nonlinear dynamical systems
Applied Mathematics and Computation - Special issue on dynamics and control
Parametric identification of robotic systems with stable time-varying Hopfield networks
Neural Computing and Applications
Hopfield Neural Networks for Parametric Identification of Dynamical Systems
Neural Processing Letters
System Identification of Dengue Fever Epidemics in Cuba
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
HIV Model Described by Differential Inclusions
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Robustness of the "hopfield estimator" for identification of dynamical systems
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
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This paper presents a method for estimation of parameters in dynamical systems, applied to a model of the HIV-AIDS epidemics in Cuba. This estimation technique, based upon artificial neural networks, has been successfully applied to robotic systems, whereas the application to epidemiological models is challenged by the possible uncertainty of the model; besides, a state variable exists that is not directly measurable. With regard to the first limitation, a model provided by experts, previously validated by statistical techniques, has been used; with respect to the second drawback, an evaluation of the unknown variable has been carried out from comparisons with other models of the development of the disease. Among the parameters that intervene in the model, three important factors have been considered: the detection rate of the disease, through the contact tracing program; the detection rate through other methods; and the rate of transition to AIDS of previously undetected infected individuals. Results are plausible, according to experts, and they support both the estimation method and the model.