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Information Technologies and Control

The Journal of Institute of Information and Communication Technologies of Bulgarian Academy of Sciences

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General Forms of a Class of Multivariable Regression Models

A. Efremov
Published Online: 2014-10-02 | DOI: https://doi.org/10.2478/itc-2013-0009


There are two possible general forms of multiple input multiple output (MIMO) regression models, which are either linear with respect to their parameters or non-linear, but in order to estimate their parameters, at a certain stage it could be assumed that they are linear. This is in fact the basic assumption behind the linear approach for parameters estimation. There are two possible representations of a MIMO model, which at a certain level could be fictitiously presented as linear functions of its parameters. One representation is when the parameters are collected in a matrix and hence, the regressors are in a vector. The other possible case is the parameters to be in a vector, but the regressors at a given instant to be placed in a matrix. Both types of representations are considered in the paper. Their advantages and disadvantages are summarized and their applicability within the whole experimental modelling process is also discussed.

Keywords: MIMO model; linear parameterization; parameter matrix form; parameter vector form; stepwise regression


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About the article

Received: 2013-12-18

Published Online: 2014-10-02

Citation Information: Information Technologies and Control, Volume 11, Issue 2, Pages 22–28, ISSN (Online) 1312-2622, DOI: https://doi.org/10.2478/itc-2013-0009.

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© 2013 A. Efremov. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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