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Conference item

EEG analysis using self-organisation

Abstract:
We have shown that the use of a self-organising feature map has enabled clustring of feature vectors in a high dimensional space, from a highly complex signal, about which little prior knowledge is known. We have also demonstrated that the transition trajectories between the main cluster sites are representative of three competing dynamic processes which govern the gross structure of the EEG during sleep. We are now in the position to apply this method to clinical situations for which it has hitherto been impossible to analyse the sleep EEG.

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Publisher:
Publ by IEE
Host title:
IEE Conference Publication
Issue:
349
Pages:
210-213
Publication date:
1991-01-01
ISSN:
0537-9989
Pubs id:
pubs:318958
UUID:
uuid:699d8d4d-c460-4d6c-8739-10dda358d03c
Local pid:
pubs:318958
Source identifiers:
318958
Deposit date:
2013-11-17

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