Conference: Inverse Problems in Engineering Author: Trond Mannseth Affiliation: Rf-rogaland Research Title: Nonlinearity, Scale, and Sensitivity for Parameter Estimation Problems; Some Implications for Estimation Algorithms

Author: Trond Mannseth Affiliation: RF-Rogaland Research Title: NONLINEARITY, SCALE, AND SENSITIVITY FOR PARAMETER ESTIMATION PROBLEMS; SOME IMPLICATIONS FOR ESTIMATION ALGORITHMS Text: Parameter estimation algorithms that rely on sensitivity information to calculate new parameter updates, are usually based on a linearization of the model function at the current parameter estimate. Hence, both sensitivity and nonlinearity are of importance for the efficiency of the estimation algorithm. Therefore, knowledge of a general nature on sensitivity and/or nonlinearity for some class of models can perhaps be utilized to improve the estimation efficiency for this class.