An Approach to RBF Initialization with Feature Selection-Reference-Cited by-同舟云学术

An Approach to RBF Initialization with Feature Selection

Published:2015 Issue: Volume: Page:671-682
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
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Author:

Czarnowski Ireneusz,Jędrzejowicz Piotr

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-11313-5_59

Reference26 articles.

1. Broomhead, D.S., Lowe, D.: Multivariable Functional Interpolation and Adaptive Networks. Complex Systems 2, 321–355 (1988)

2. Lecture Notes in Computer Science;H. Gao,2006

3. Wilson, D.R., Martinez, T.R.: Heterogeneous Radial Basis Function Networks. In: Proceedings of the International Conference on Neural Networks (ICNN 1996), vol. 2, pp. 1263–1267 (1996)

4. STUDFUZZ;L. Wang,2005

5. Asuncion, A., Newman, D.J.: UCI Machine Learning Repository. University of California, School of Information and Computer Science, Irvine (2007), http://www.ics.uci.edu/~mlearn/MLRepository.html (accessed June 24, 2009)

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