A UNIFYING THEORY OF LEAST-SQUARES PADE MODEL-REDUCTION METHODS

The apparently different approaches of least-squares parameter-matchin g Pade model reduction methods are shown to be related via a unifying theory. From the formulation it is possible to show several interestin g features of the least-squares approach which lead to a fuller unders tanding of exactly how the reduced model approximates the system. An e rror index is derived for the general case and it is shown that a rang e of system parameter preservation options are available to the user. A numerical example illustrates the main points of the paper.