Journal article
Stochastic complexity measures for physiological signal analysis.
- Abstract:
- Traditional feature extraction methods describe signals in terms of amplitude and frequency. This paper takes a paradigm shift and investigates four stochastic-complexity features. Their advantages are demonstrated on synthetic and physiological signals; the latter recorded during periods of Cheyne-Stokes respiration, anesthesia, sleep, and motor-cortex investigation.
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- Publisher copy:
- 10.1109/10.709563
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Authors
Bibliographic Details
- Publisher:
- IEEE
- Journal:
- IEEE transactions on bio-medical engineering
- Volume:
- 45
- Issue:
- 9
- Pages:
- 1186-1191
- Publication date:
- 1998-09-01
- DOI:
- EISSN:
-
1558-2531
- ISSN:
-
0018-9294
- Source identifiers:
-
318883
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
pubs:318883
- UUID:
-
uuid:23557686-b58f-422d-b05f-aad5cf3e74b0
- Local pid:
- pubs:318883
- Deposit date:
- 2012-12-19
Terms of use
- Copyright date:
- 1998
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