Abstract
This chapter is central to this book and describes how to compute system matrices of state space models from given sets of time series data. The dimensions of the models are determined by the numerical ranks of the Hankel matrices constructed from the sample covariance matrices of data sets. In this way the dimensions of the models are data determined. Among equivalent representations of models of given dimensions, the one called (intenally) balanced is chosen for its advantages in conducting error analysis and in constructing lower dimensional approximate models.
The erratum of this chapter is available at http://dx.doi.org/10.1007/978-3-642-96985-0_13
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© 1987 Springer-Verlag Berlin Heidelberg
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Aoki, M. (1987). Computation of System Matrices. In: State Space Modeling of Time Series. Universitext. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-96985-0_9
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DOI: https://doi.org/10.1007/978-3-642-96985-0_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-17257-4
Online ISBN: 978-3-642-96985-0
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