DocumentCode :
2706857
Title :
Extreme value statistics for novelty detection in biomedical signal processing
Author :
Roberts, Stephen J.
Author_Institution :
Dept. of Eng. Sci., Oxford Univ., UK
fYear :
2000
fDate :
2000
Firstpage :
166
Lastpage :
172
Abstract :
The issue of determining whether some datum is indicative of abnormal or novel system behaviour is paramount in areas such as medical data analysis where the acquisition of large quantities of abnormal data is difficult. Several approaches to screening data for such novel segments have been proposed previously. However, extreme-value theory (EVT) and its associated statistics provide a complete and principled approach to the problem which avoids the need for heuristic methods. EVT forms an elegant methodology for any problem in which the chance of finding extremes of some quantity is required
Keywords :
biocybernetics; medical signal processing; statistical analysis; abnormal data acquisition; abnormal system behaviour; biomedical signal processing; data screening; extreme value statistics; medical data analysis; novelty detection; outliers;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Advances in Medical Signal and Information Processing, 2000. First International Conference on (IEE Conf. Publ. No. 476)
Conference_Location :
Bristol
ISSN :
0537-9989
Print_ISBN :
0-85296-728-4
Type :
conf
DOI :
10.1049/cp:20000333
Filename :
889967
Link To Document :
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