Functional Canonical Analysis Between Functional and Interval Data

Yow-Jen Jou*, Chien-Chia Huang, Jennifer Yuh Jen Wu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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.
Original languageEnglish
Title of host publicationCOMPUTATIONAL METHODS IN SCIENCE AND ENGINEERING, VOL 2: ADVANCES IN COMPUTATIONAL SCIENCE
Subtitle of host publicationLectures presented at the International Conference on Computational Methods in Sciences and Engineering 2008 (ICCMSE 2008)
EditorsG Maroulis, TE Simos
Pages453-457
Number of pages5
Volume1148
DOIs
StatePublished - 25 Sep 2009
Event6th International Conference on Computational Methods in Sciences and Engineering 2008, ICCMSE 2008 - Hersonissos, Crete, Greece
Duration: 25 Sep 200830 Sep 2008

Publication series

NameAIP Conference Proceedings
Volume1148
ISSN (Print)0094-243X

Conference

Conference6th International Conference on Computational Methods in Sciences and Engineering 2008, ICCMSE 2008
Country/TerritoryGreece
CityHersonissos, Crete
Period25/09/0830/09/08

Keywords

  • Canonical Correlation Analysis (CCA)
  • Interval data
  • Functional data

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