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A method of parameter identification for dynamic systems based on model output minimum entropy

Liu, T.Y. and Jia, J.F. and Wang, H. and Yue, H. (2007) A method of parameter identification for dynamic systems based on model output minimum entropy. In: 26th Chinese Control Conference, 2007-07-26 - 2007-07-31.

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Parameter estimation is important in mathematical modeling. The Maximum Likelihood method can be used when the probability density function of observation is known. However, this assumption may not be satisfied in practice. To deal with this problem, a new parameter estimation method for dynamic systems is proposed using the entropy of probability density function for system output viable and two performance functions are also given. To illustrate the effectiveness of this method, HIV/AIDS model is taken as an example to evaluate simulation and results are encouraging.