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Proceedings Paper

Nonlinear calibration with genetic optimizing RBF neural network
Author(s): Wu Wang; Li-Hui Guo; Xiao-bo Jiao
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Paper Abstract

Virtual instrument was widely used in automatic measurement and control system, nonlinear calibration was necessary in the science research and high-precise measurement. Nonlinear calibration method with RBFNN was proposed in this paper for ANN's ability of self-learning and generalization and GA was introduced to optimize its structure and parameters. The structure of RBFNN was created and optimizing algorithm was proposed, the fundamental of nonlinear calibration was introduced. The simulation shows RBFNN with optimized by GA can greatly increase the convergence speed and precision, nonlinear calibration with ANN was feasible and the precision was obviously improved, this method can be used into automatic measure system effectively.

Paper Details

Date Published: 28 October 2011
PDF: 5 pages
Proc. SPIE 8205, 2011 International Conference on Photonics, 3D-Imaging, and Visualization, 82051F (28 October 2011); doi: 10.1117/12.905833
Show Author Affiliations
Wu Wang, Xu Chang Univ. (China)
Li-Hui Guo, Xu Chang Univ. (China)
Xiao-bo Jiao, Xuchang Electric Power Co. (China)


Published in SPIE Proceedings Vol. 8205:
2011 International Conference on Photonics, 3D-Imaging, and Visualization
Egui Zhu, Editor(s)

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