Hierarchical gradient based iterative parameter estimation algorithm for multivariable output error moving average systems
According to the hierarchical identification principle, a hierarchical gradient based iterative estimation algorithm is derived for multivariable output error moving average systems (i.e., multivariable OEMA-like models) which is different from multivariable CARMA-like models. As there exist unmeasurable noise-free outputs and unknown noise terms in the information vector/matrix of the corresponding identification model, this paper is, by means of the auxiliary model identification idea, to replace the unmeasurable variables in the information vector/matrix with the estimated residuals and the outputs of the auxiliary model. A numerical example is provided. (C) 2010 Elsevier Ltd. All rights reserved.
parameter estimation hierarchical identification multivariable oema-like model multivariable carma-like model iterative algorithm jacobi iteration matrix equation gradient search iterative identification