State and parameter estimation for nonlinear biological phenomena modeled by S-systems
Propose new improved particle filtering based on minimizing the KullbackLeibler divergence distance. Apply the developed techniques to estimate states and parameters in biology process model representing Cad System in E. coli. Investigate the effects of practical challenges on the performances of developed techniques. Comparative performance analysis of various state-of-the-art state estimation techniques.
state and parameter estimation improved particle filtering cad system in e. coli nonlinear biological systems