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Extreme value statistics for novelty detection in biomedical signal processing

Abstract:
Extreme value theory (EVT) is a branch of statistics which concerns the distributions of data of unusually low or high value i.e. in the tails of some distribution. These extremal points are important in many applications as they represent the outlying regions of normal events against which we may wish to define novel events. The use of such novelty detection approaches is useful for analysis of data for which few exemplars of some important class exist, for example in medical screening. It is shown that a principled approach to the issue of novelty detection may be taken using extreme value statistics.
Publication status:
Published

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Publisher copy:
10.1049/ip-smt:20000841

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Role:
Author, Author


Publisher:
IEE
Host title:
FIRST INTERNATIONAL CONFERENCE ON ADVANCES IN MEDICAL SIGNAL AND INFORMATION PROCESSING
Volume:
147
Issue:
476
Pages:
166-172
Publication date:
2000-01-01
DOI:
ISSN:
0537-9989
ISBN:
0852967284


Pubs id:
pubs:62855
UUID:
uuid:175e7299-18c6-487c-bf53-d4445c3dd7e1
Local pid:
pubs:62855
Source identifiers:
62855
Deposit date:
2012-12-19
ARK identifier:

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