An information-theoretic input selection method for dynamical system modeling is presented that qualifies the rejection of irrelevant inputs from a candidate input set with an estimate of a measure of confidence given only finite data. To this end, we introduce a method of determining the spatial interval of dependency in the context of the modeling problem for bootstrap mutual information estimates on dependent time-series. Additionally, details are presented for determining an optimal binning interval for histogram-based mutual information estimates.
|Number of pages
|Proceedings of the American Control Conference
|Published - Nov 29 2004
|Proceedings of the 2004 American Control Conference (AAC) - Boston, MA, United States
Duration: Jun 30 2004 → Jul 2 2004
ASJC Scopus subject areas
- Electrical and Electronic Engineering