Proceedings of the Third International Conference on Soft Computing for Problem Solving pp 459-466 | Cite as
Reconstruction of Noisy Bezier Curves Using Artificial Neural Networks
Conference paper
First Online:
Abstract
The current work examines the reconstruction of Bezier curves with noisy data using artificial neural networks. Feed forward network with back propagation learning is used to fit the noisy data of the Bezier curves. Different parameters like learning rate, number of hidden layer neurons and number of epochs are studied and the results are compared for different runs. The best suited parameters are established for this specific problem.
Keywords
Bezier curve Feed-forward network Noisy data Back-propagation learningReferences
- 1.Rogers, D.F., Adams, J.A.: Mathematical Elements of Computer Graphics. Tata Mc Graw Hill Publications, New Delhi (1990)Google Scholar
- 2.Uys, E.: An investigation into using neural networks for statistical classificationandre regression. University of Pretoria, Pretoria (2010)Google Scholar
- 3.Paliwal, Mukta, Kumar, Usha A.: Neural networks and statistical techniques: a review of applications. Expert Syst. Appl. 36(1), 2–17 (2009)CrossRefGoogle Scholar
- 4.Liu1, X., Huang, H., Xu, W.: Approximate B-Spline Surface Based on RBF Neural Networks. Lecture Notes in Computer Science, vol 3514, pp. 995–1002. Springer, Heidelberg (2005)Google Scholar
Copyright information
© Springer India 2014