This work uses synchronization along with numerical optimization to determine unmeasured state variables and parameters in a multi-dimensional system. One (or more) of the system dynamical variables is(are) measured, and then coupled into model equations for the system. A cost function is constructed to minimize the coupling and the error between the model and experimental values.