期刊
TECHNOMETRICS
卷 43, 期 1, 页码 1-9出版社
AMER STATISTICAL ASSOC
DOI: 10.1198/00401700152404273
关键词
basis functions; classification; dimension reduction; discrimination; discriminant analysis; functional data analysis; kernel methods; nonparametric density estimation; odds ratio; radar range profiles; signal analysis
Motivated by specific problems involving radar-range profiles, we suggest techniques for real-time discrimination in the context of signal analysis. The key to our approach is to regard the signals as curves in the continuum and employ a functional data-analytic (FDA) method for dimension reduction, based on the FDA technique for principal coordinates analysis. This has the advantage, relative to competing methods such as canonical variates analysis, of providing a signal approximation that is best possible, in an L-2 sense, for a given dimension. As a result, it produces particularly good discrimination. We explore the use of both nonparametric and Gaussian-based discriminators applied to the dimension-reduced data.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据