完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Jou, Yow-Jen | en_US |
dc.contributor.author | Huang, Chien-Chia | en_US |
dc.contributor.author | Wu, Jennifer Yuh-Jen | en_US |
dc.date.accessioned | 2014-12-08T15:18:43Z | - |
dc.date.available | 2014-12-08T15:18:43Z | - |
dc.date.issued | 2009 | en_US |
dc.identifier.isbn | 978-0-7354-0685-8 | en_US |
dc.identifier.issn | 0094-243X | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/13457 | - |
dc.description.abstract | In this study we discuss the functional canonical correlation analysis between the functional data and the interval data. To address the interval data, a representative is of necessity. Based on the work by Chavent et al. (2002), the representative can be derived by using the Hausdorff distance between intervals. The canonical analysis can be either the mixed functional-multivariate canonical correlation analysis or a pure functional one. This approach is then applied to the roadside vehicle detection by using Radar devices. It can be observed that the weight functions implicitly contain the information about the distances between the specific lane and the detector. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Interval data | en_US |
dc.subject | Functional data | en_US |
dc.subject | Canonical Correlation Analysis (CCA) | en_US |
dc.title | Functional Canonical Analysis Between Functional and Interval Data | en_US |
dc.type | Article | en_US |
dc.identifier.journal | COMPUTATIONAL METHODS IN SCIENCE AND ENGINEERING, VOL 2: ADVANCES IN COMPUTATIONAL SCIENCE | en_US |
dc.citation.volume | 1148 | en_US |
dc.citation.spage | 453 | en_US |
dc.citation.epage | 457 | en_US |
dc.contributor.department | 資訊管理與財務金融系 註:原資管所+財金所 | zh_TW |
dc.contributor.department | Department of Information Management and Finance | en_US |
dc.identifier.wosnumber | WOS:000280417500113 | - |
顯示於類別: | 會議論文 |