DocumentCode :
2570162
Title :
System identification of a circadian signal source using BP neural networks
Author :
Cisse, Y. ; Kinouchi, Y. ; Nagashino, H. ; Akutagawa, M.
Author_Institution :
Dept. of Electr. & Electron. Eng., Tokushima Univ., Japan
Volume :
6
fYear :
1998
fDate :
29 Oct-1 Nov 1998
Firstpage :
3032
Abstract :
The dynamics of some biological signal sources may be identified through measured data. The regulating characteristics of the wake-sleep circadian rhythm is identified here as an example by using BP neural networks. As a result, a MA model of neural networks can acquire the characteristics. The change of wake-sleep period is almost controlled suppressively by the data of preceding three days. The change of the dynamics can be evaluated by internal representation of the network. This method may be useful for medical diagnoses
Keywords :
backpropagation; biocontrol; identification; moving average processes; neural nets; neurophysiology; nonlinear dynamical systems; physiological models; sleep; autonomous oscillator; backpropagation neural networks; biological signal source dynamics; circadian signal source; internal representation; medical diagnoses; nonlinear moving average model; regulating characteristics; system identification; vector representation; wake-sleep circadian rhythm; Biological neural networks; Circadian rhythm; Fluctuations; Medical diagnosis; Neural networks; Neurons; Oscillators; Signal processing; System identification; Time measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE
Conference_Location :
Hong Kong
ISSN :
1094-687X
Print_ISBN :
0-7803-5164-9
Type :
conf
DOI :
10.1109/IEMBS.1998.746130
Filename :
746130
Link To Document :
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