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Improved system identification with Renormalization Group
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DOI：10.1016/j.isatra.2013.10.003.png)
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Abstract
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This paper proposes an improved system identification method with Renormalization Group. Renormalization Group is applied to a fine data set to obtain a coarse data set. The least squares algorithm is performed on the coarse data set. The theoretical analysis under certain conditions shows that the parameter estimation error could be reduced. The proposed method is illustrated with examples. (C) 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Keywords:
System identification
Least squares estimate
Renormalization Group
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