Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2824-2829 |
| Number of pages | 6 |
| Journal | Proceedings of the American Control Conference |
| Volume | 3 |
| State | Published - 2004 |
| Externally published | Yes |
| Event | 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