Title :
Robust parametric estimation for nonlinear models using artificial neural networks
Author :
Silva, Ivan N. ; Amaral, Wagner C. ; Arruda, Lucia V R
Author_Institution :
School of Electr. & Comput. Eng., Univ. of Campinas, Brazil
Abstract :
The paper describes an approach using artificial neural networks for solving problems of robust parametric estimation with unknown-but-bounded error (UBBE approach). A modified Hopfield network is used to calculate the parametric uncertainty intervals for the model parameters. Simulated examples are presented as an illustration of the proposed technique
Keywords :
Hopfield neural nets; nonlinear systems; parameter estimation; statistical analysis; uncertain systems; UBBE approach; artificial neural networks; model parameters; modified Hopfield network; nonlinear models; parametric uncertainty intervals; proposed technique; robust parametric estimation; simulated examples; unknown-but-bounded error; Additive noise; Artificial neural networks; Computer industry; Computer networks; Cost function; Noise measurement; Parameter estimation; Robustness; Uncertainty; Vectors;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.633264
