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

T.Y. Liu, J.F. Jia, H. Wang, H. Yue

Research output: Contribution to conferencePaper

Abstract

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.
Original languageEnglish
Pages112-114
Number of pages2
DOIs
Publication statusPublished - 2007
Event26th Chinese Control Conference - Zhangjiajie, China
Duration: 26 Jul 200731 Jul 2007

Conference

Conference26th Chinese Control Conference
CountryChina
CityZhangjiajie
Period26/07/0731/07/07

Keywords

  • dynamic systems
  • histogram
  • probability density function
  • entropy
  • parameter estimation

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