Identification of parameters in initial value problems for ordinary differential equations

Chleboun, Jan, and Mikeš, Karel. "Identification of parameters in initial value problems for ordinary differential equations." Programs and Algorithms of Numerical Mathematics. Prague: Institute of Mathematics AS CR, 2015. 58-63. <http://eudml.org/doc/269922>.

@inProceedings{Chleboun2015,
abstract = {Scalar parameter values as well as initial condition values are to be identified in initial value problems for ordinary differential equations (ODE). To achieve this goal, computer algebra tools are combined with numerical tools in the MATLAB environment. The best fit is obtained through the minimization of the summed squares of the difference between measured data and ODE solution. The minimization is based on a gradient algorithm where the gradient of the summed squares is calculated either numerically or via auxiliary initial value problems. In the latter case, the MATLABR Symbolic Math Toolbox is used to derive the expressions that define the auxiliary problems and to transform them into MATLAB routines.},
author = {Chleboun, Jan, Mikeš, Karel},
booktitle = {Programs and Algorithms of Numerical Mathematics},
keywords = {computer algebra; gradient algorithm},
location = {Prague},
pages = {58-63},
publisher = {Institute of Mathematics AS CR},
title = {Identification of parameters in initial value problems for ordinary differential equations},
url = {http://eudml.org/doc/269922},
year = {2015},
}

TY - CLSWK
AU - Chleboun, Jan
AU - Mikeš, Karel
TI - Identification of parameters in initial value problems for ordinary differential equations
T2 - Programs and Algorithms of Numerical Mathematics
PY - 2015
CY - Prague
PB - Institute of Mathematics AS CR
SP - 58
EP - 63
AB - Scalar parameter values as well as initial condition values are to be identified in initial value problems for ordinary differential equations (ODE). To achieve this goal, computer algebra tools are combined with numerical tools in the MATLAB environment. The best fit is obtained through the minimization of the summed squares of the difference between measured data and ODE solution. The minimization is based on a gradient algorithm where the gradient of the summed squares is calculated either numerically or via auxiliary initial value problems. In the latter case, the MATLABR Symbolic Math Toolbox is used to derive the expressions that define the auxiliary problems and to transform them into MATLAB routines.
KW - computer algebra; gradient algorithm
UR - http://eudml.org/doc/269922
ER -