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Consistency of the structured total least squares estimator in a multivariate errors-in-variables model
Institution:1. School of Computer and Control Engineering, YanTai University, YanTai, China;2. Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China;3. School of Computer Science and Engineering, Hebei University of Technology, Tianjin, China;4. The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang, China
Abstract:The structured total least squares estimator, defined via a constrained optimization problem, is a generalization of the total least squares estimator when the data matrix and the applied correction satisfy given structural constraints. In the paper, an affine structure with additional assumptions is considered. In particular, Toeplitz and Hankel structured, noise free and unstructured blocks are allowed simultaneously in the augmented data matrix. An equivalent optimization problem is derived that has as decision variables only the estimated parameters. The cost function of the equivalent problem is used to prove consistency of the structured total least squares estimator. The results for the general affine structured multivariate model are illustrated by examples of special models. Modification of the results for block-Hankel/Toeplitz structures is also given. As a by-product of the analysis of the cost function, an iterative algorithm for the computation of the structured total least squares estimator is proposed.
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