Neural network modeling of ambulatory systolic blood pressure for hypertension diagnosis-Reference-Cited by-同舟云学术

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Neural network modeling of ambulatory systolic blood pressure for hypertension diagnosis

Published:2003 Issue: Volume: Page:599-606
ISSN:0302-9743
Container-title:Artificial Neural Nets Problem Solving Methods
language:
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Author:

Hosseini Shahram,Jutten Christian,Charbonnier Sylvie

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-44869-1_76

Reference5 articles.

1. S. Charbonnier, S. Galichet, G. Mauris and J-P Siche, Statistical and fuzzy models of ambulatory systolic blood pressure for hypertension diagnosis. IEEE Trans. on Instrumentation and Measurement, vol. 49, no. 5,pp. 998–1003, Oct. 2000.

2. T.Y. Kwok and D.Y. Yeung, Constructive Algorithms for Structure Learning in Feedforward Neural Networks for Regression Problems. IEEE Trans. on Neural Networks, vol. 8, no. 3, May 1997.

3. G. Cybenko, Approximation by superposition of sigmoidal functions, Mathematics of Control, Signals and Systems, vol. 2, pp. 303–314, 1989.

4. S. Hosseini and C. Jutten, Maximum likelihood neural approximation in presence of additive colored noise, IEEE Trans. on Neural Networks, vol. 13, no. 1, pp. 117–131, Jan. 2002.

5. R. F. Galbraith and J. I. Galbraith, On the inverse of some patterned matrices arising in the theory of stationary time series, Journal of Applied Probability, vol. 11, pp. 63–71, 1974.

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