Linear regression techniques for state-space models with application to biomedical/biochemical example

N. Khairudin, K.J. Keesman

Research output: Chapter in Book/Report/Conference proceedingConference paper

Abstract

In this paper a novel approach to estimate parameters in an LTI continuous-time statespace model is proposed. Essentially, the approach is based on a so-called pqR-decomposition of the numerator and denominator polynomials of the system’s transfer function. This approach allows the physical knowledge of the system to be preserved. As an illustrative example, a biomedical/biochemical process with two compartments in parallel and with first-order reaction is used.First, the process is approximated by a discrete-time state-space model. Next, after deriving the corresponding discrete-time transfer function, the rational transfer function is decomposed into pqR form and then reparametrized to obtain a set of linear regressive equations. Subsequently, the unknown linear regression parameters, which are a polynomial function of the original physical parameters, are uniquely estimated from real data of the biomedical/biochemical process using the ordinary least-squares method. This approach is favourable when there is a need to preserve physical interpretations in the parameters. Furthermore, by taking into account the original model structure, a smaller number of parameters than in the case of direct transfer function estimation may result and the identifiability property naturally appears.
Original languageEnglish
Title of host publicationProceedings of the 6th Vienna International Conference on Mathematical Modelling, Vienna, Austria, 11-13 February 2009
Place of PublicationVienna
PublisherVienna University of Technology
Pages1513-1520
ISBN (Print)9783901608353
Publication statusPublished - 2009
Event6th Vienna Conference on Mathematical Modelling, Vienna, Austria -
Duration: 11 Feb 200913 Feb 2009

Conference

Conference6th Vienna Conference on Mathematical Modelling, Vienna, Austria
Period11/02/0913/02/09

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