System classification by using discriminant functions of time-frequency features

被引：0
|
作者：
Mendoza Reyes, Miguel
Lorenzo-Ginori, Juan V.
Taboada-Crispi, A.
Luna Carvajal, Yakelin
机构：
[1] Univ Cent Marta Abreu Las Villas, Ctr Studies Elect & Informat Technol, Santa Clara 54830, VC, Cuba
[2] Minist Publ Hlth, Santa Clara, VC, Cuba
来源：
PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS AND APPLICATIONS, PROCEEDINGS | 2006年 / 4225卷
关键词：
time-frequency distributions; feature extraction;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Time-frequency representations (TFR) convey relevant information about systems that can not be obtained under stationary conditions. In this paper, a methodology to classify systems using the information obtained from time-frequency representations during transient phenomena is described and tested experimentally. The study includes an assessment of the features to be extracted from the TFR, which are relevant for the desired classification, as well as the construction of the appropriate discriminant functions using them. The methodology is tested by means of a biomedical example related to patient's classification.
引用
收藏
页码：920 / 928
页数：9
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