Semi-Empirical Modeling of Non-Linear Dynamic Systems through Identification of Operating Regimes and Local Models-Reference-Cited by-同舟云学术

Semi-Empirical Modeling of Non-Linear Dynamic Systems through Identification of Operating Regimes and Local Models

Published:1995 Issue: Volume: Page:105-126
ISSN:1430-9491
Container-title:Neural Network Engineering in Dynamic Control Systems
language:
Short-container-title:

Author:

Johansen Tor A.,Foss Bjarne A.

Publisher

Springer London

Link

http://link.springer.com/content/pdf/10.1007/978-1-4471-3066-6_6.pdf

Reference32 articles.

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3. M. Carlin, T. Kavli, and B. Lillekjendlie. A comparison of four methods for nonlinear data modeling. Chemometrics and Int. Lab. Sys., 23:163–178, 1994.

4. P. Craven and G. Wahba. Smoothing noisy data with spline functions. Estimating the correct degree of smoothing by the method of generalized cross-validation. Numerical Math., 31:317–403, 1979.

5. R. D. De Veaux, D. C. Psichogios, and L. H. Ungar. A tale of two nonparametric estimation schemes: MARS and neural networks. In Proc. 4th Int. Conf. Artificial Intelligence and Statistics, 1993.

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