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Content Provider | IEEE Xplore Digital Library |
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Author | Chiuso, A. |
Copyright Year | 2006 |
Description | Author affiliation: Dipt. di Tecnica e Gestione dei Sistemi Industriali, Universita di Padova, Vicenza (Chiuso, A.) |
Abstract | Some subspace procedures make use, directly or indirectly, of Vector AutoRegressive with eXogenous inputs (VARX) models in a preliminary step. This was first noticed for the CCA method; more recently it has also been proved that the first oblique projection step of a subspace algorithm based on predictor identification (PBSID) is asymptotically equivalent to the SSARX algorithm by Jansson which performs a preliminary VARX modeling step. For the purpose of comparison with more classical methods like CCA a recent work have introduced also an "optimized" version of PBSID. In this paper we shall show that indeed also this latter "optimized" PBSID is equivalent to estimating a long VARX model followed by the "classical" steps of subspace identification. This latter step can be seen as a sort of model reduction. Besides the theoretical interest, we shall argue that this may have also important implications regarding computational complexity |
Starting Page | 3646 |
Ending Page | 3651 |
File Size | 223754 |
Page Count | 6 |
File Format | |
ISBN | 1424401712 |
DOI | 10.1109/CDC.2006.377744 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2006-12-13 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Reduced order systems Optimization methods Reactive power Prediction algorithms Predictive models Computational complexity USA Councils Statistical analysis Performance analysis Algorithm design and analysis Subspace Methods Identification Statistical Analysis |
Content Type | Text |
Resource Type | Article |
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